Impact of Music Expression-Related Parameters on Pianists’ Kinematics and Muscle Activity: A Systematic Review

Impact of Music Expression-Related Parameters on Pianists’ Kinematics and Muscle Activity: A Systematic Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Impact of Music Expression-Related Parameters on Pianists’ Kinematics and Muscle Activity: A Systematic Review Robin Mailly, Craig Turner, Etienne Goubault, Fabien Dal Maso, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5204526/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Feb, 2025 Read the published version in Music & Science → Version 1 posted You are reading this latest preprint version Abstract Bodily gestures are essential in piano performance. They allow sound production and, at the same time, facilitate the communication of the expressive content of music. From pianists’ perspective, music expression-related parameters include not only single performance parameters (timing, sound intensity, articulation, etc.), but also more complex parameters (named hereafter abstract parameters), such as music structure features (e.g., phrasing) and extra-musical ideas (e.g., emotions, narratives, etc.). This systematic review aimed to investigate the impact of both performance and abstract parameters related to music expression on kinematics and muscle activity of expert pianists. As complementary objectives, we documented ontological and methodological differences between the studies included, and we addressed how music expression-related parameters affect pianists’ exposure to risk factors of injuries. The search strategy consisted of using concepts and keywords in Medline, Embase, SPORTDiscus, and Web of Science databases, and we followed the PRISMA guidelines. Fifteen studies were included. Ten studies focused on performance parameters, four studies focused on abstract parameters, and one study addressed both performance and abstract parameters. Performance and abstract music expression-related parameters impacted pianists’ kinematics and muscle activity in a variety of ways. The specific effects were dependent on the type of task and the gestural variable investigated by studies. Important differences in ontological (performance or abstract parameters studied, gestural variable investigated) and methodological choices (experimental task and instrument used, data acquisition and processing procedures) prevent the establishment of a thorough dialogue between music research studies and biomechanics and motor control studies. A set of performance parameters (playing loud, playing fast, staccato articulation, large handspan chords) were identified as potential risk factors of injuries. Further interdisciplinary research mixing methods from empirical music research and biomechanics would help enhance knowledge on the impact of music expression on pianists’ gestures for both performance and injury prevention purposes. Music Sports Medicine and Kinesiology piano performance expressive intentions biomechanics EMG PRMDs Figures Figure 1 Figure 2 Introduction In music research, musicians’ body movements are usually characterized as gestures. The notion of gesture encompasses both the physical movement and its mental or cognitive aspects (e.g., expression of an idea or meaning; Jensenius et al., 2010 ). Analyzing pianists’ gestures is complex, as a great variety of multi-joint kinematic strategies and muscular activities can be used to produce a single piano tone (Furuya & Altenmüller, 2013 ). Moreover, the literature suggests that amateur and expert pianists show different movement strategies and muscle recruitment while playing similar tasks (Furuya et al., 2011 ; Furuya & Kinoshita, 2007 ). Musicians’ gestures during performance have been classified according to their function. Four functional categories of musical gestures have been reported in the literature: sound-producing gestures, sound-facilitating gestures, communicative gestures, and sound-accompanying gestures (Dahl et al., 2010 ; Jensenius et al., 2010 ). Sound-producing gestures are responsible for the effective production of sound (e.g., the striking of a piano key). Sound-facilitating gestures usually refer to bodily movements used to support sound-producing gestures for different music expression needs (e.g., the coordinated movements of musicians’ arms and trunk to shape the musical phrasing of the performance). These gestures are also called ancillary gestures in the relevant literature (Wanderley & Depalle, 2004 ). Communicative gestures are intended for communication with another performer and/or with the audience. Finally, sound-accompanying gestures are made in response to the music. Sound-producing and sound-facilitating gestures have been the primary object of study in the experimental research focusing on musicians’ gestures. These two gestural functions have been typically associated to different music expression-related parameters. Music expression is a complex concept encompassing different phenomena and can be studied from a variety of disciplines (music theory, musicology, semiotic, semantics, psychology, neurosciences, performance science, biomechanics, among others). From pianists’ perspective, music expression-related parameters can be grouped in at least two main categories. First, performance parameters such as rhythm and timing (related to timing management at both micro and macro levels of a musical piece; Repp, 1998 ), sound intensity (Drake & Palmer, 1993 ), and articulation (Repp, 1995 ). This type of parameters are often called performance parameters because they are sound features effectively manipulated by pianists during practice and performance (i.e., piano tones can be louder/softer, longer/shorter, and time between tones can be longer/shorter). While performance parameters are defined (at a certain extent) by the composer in the musical score, pianists shape their performance of musical pieces by modulating these parameters according to their personal interpretation of the score (Bernays & Traube, 2014 ; Canazza et al., 1997 ; Palmer, 1996 ; Repp, 1998 ). Pianists’ sound-producing gestures are generally associated with the effective control of performance parameters and have been investigated by research focusing on music biomechanics and motor control (Furuya & Altenmüller, 2013 ; Goebl, 2017 ). The main goal of this body of literature is to assess if the manipulation of performance parameters may have an impact on exposure to risk factors of playing-related musculoskeletal disorders (PRMDs) (e.g., Degrave et al., 2020 ; Furuya et al., 2012 ; Turner et al., 2021 ). This is an important topic for musicians, as lifetime prevalence of PRMDs ranges between 62% and 93% among professional instrumentalists (Kok et al., 2016 ). However, no study has yet synthesised the current findings on the impact of performance parameters on pianists’ kinematics and muscle activity. Music performance implies not only the effective control of performance parameters, but also the production and communication of more complex artistic content (either musical or extra-musical). Therefore, a second category of music expression-related parameters is needed to account for this essential aspect of the creative work of music performers. This category encompasses both music structure elements and concepts (e.g., phrasing, melodic and harmonic tension; Bigand & Parncutt, 1999 ) and extra-musical or semantic content (extra-musical ideas, such as a specific narrative, a picture, an emotion, a physical movement metaphor, and so on; Héroux & Fortier, 2015 ; Juslin & Västfjäll, 2008 ). As these music expression-related parameters usually refer to complex musical and extra-musical ideas rather than to specific parameters, we name them abstract parameters in this review for writing and reading simplification purposes. These abstract parameters are usually associated with sound-facilitating gestures in music research literature addressing musicians’ gestures, which have been studied in relation to structural music elements (e.g., phrasing and music tension; Vines et al., 2006 ) and music expression playing conditions (Davidson, 2007 ; Thompson & Luck, 2012 ; Massie-Laberge et al., 2019 ). Studies investigating sound-facilitating gestures have used various data collection tools similar to the ones used in the field of biomechanics, particularly 3D motion capture systems, while focusing often on markers’ linear kinematics rather than on more advanced methods intended to analyze human movement. These studies have shown that changes in music expression conditions (e.g., normal, exaggerated, and deadpan playing conditions) impact both movement of markers placed on performers’ body and the overall duration of the musical excerpt played (Thompson & Luck, 2012 ; Massie-Laberge et al., 2019 ). Performance and abstract parameters are closely interrelated: abstract parameters can impact or inform performers’ choices in relation to performance parameters, and changes in performance parameters might result in changes in abstract parameters. Despite this interrelated nature, the literature addressing how performance and abstract parameters influence musicians’ gestures have evolved in silos. Sound-producing gestures have been mainly addressed by studies focusing on the biomechanics of music performance, while sound-facilitating gestures have been addressed by empirical music research studies focusing on cognitive, musical, and learning aspects of music performance from an embodied cognition theoretical perspective. As a result, there is currently a lack of dialogue between the studies addressing the impact of performance and abstract parameters related to music expression on pianists’ kinematics and muscle activity. This systematic review aimed to establish a dialogue between experimental research on expert pianists’ sound-producing and sound-facilitating gestural functions through three research questions. First, we investigated how both performance and abstract parameters related to music expression impact the kinematics and muscle activity of expert pianists. Second, we addressed the following two complementary research questions: i ) what are the ontological and methodological differences between the available studies on music expression and pianists’ gestures, and ii ) how music expression-related parameters affect pianists’ exposure to risk factors of PRMDs. Methods The present systematic review was reported in accordance with Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines (Page et al., 2021 ). Search strategy A professional university librarian assisted with the creation and execution of the search strategy. Keywords within each concept were combined with the OR Boolean operator, and three concepts were combined with the AND Boolean operator (Table 1 ). The electronic databases OVID (Medline, Embase), EBSCO (SPORTDiscus with Full Text) and CLARIVATE (Web of Science) were systematically searched. The last search was performed on December 14, 2022. Following the search, all identified studies were collated and uploaded into EndNote (X9, Clarivate Analytics, USA) and duplicates were removed. Then, references were uploaded to the Web-based system review software Covidence for the study selection process. Table 1 Concept and keywords used to identify relevant articles. Concept Related keywords Participant Piano OR pianist Music expression-related parameters performance OR expressive OR expression OR “musical structure” OR “structural parameters of pieces” OR intention OR communication OR patterns OR loudness OR louder OR tempo OR tempi OR duration OR velocity OR velocities OR “sound intensity” OR timing OR rhythm OR articulation OR timbre OR “musical tension” Kinematics and muscle activity Movement OR motion OR gesture OR kinematic OR biomechanics OR electromyography OR electromyogram OR electromyograph OR muscle OR muscular OR position OR posture Eligibility criteria Publications in English in peer-reviewed journals were included. Specifically, the focus centered on experimental studies on piano involving expert or professional adult pianists. The task was required to be a musical excerpt or a series of notes, encompassing either isolated keystrokes (such as repeated notes or octaves) or technical melodic exercises (such as scale or arpeggio tasks). Consistency across participants was a key requirement: all participants were to undertake the same task. Moreover, the designated task had to incorporate at least one change in expression-related parameters: performance parameters (e.g., sound intensity, articulation, tempo), abstract parameters (e.g., use of experimental conditions such as deadpan, immobile, normal, exaggerated), or type of playing context used (e.g., tone sequences, chord sequences, etc.). Lastly, the dependent variable for analysis was required to be based on the measurement of pianist muscle activity and/or kinematics during the piano task. Conversely, studies with only novices or studies comparing novices and experts were excluded. Additionally, studies focusing on the analysis of performance parameters without a formal analysis of gestural features (muscle activity or kinematics) were excluded. Finally, studies involving duo performance were excluded (as it involves additional elements, such as synchronization and communication with the other performer, that are not present in a solo piano performance and may therefore introduce risk of interference). Study selection A first screening was performed using only titles followed by a second screening of abstracts performed by two independent reviewers (authors RM and CT). This process determined whether a study was to be included based on the predetermined eligibility criteria, while minimizing reviewer bias. Subsequently, a final sorting was performed by two authors (RM and CT) using the full texts of the remaining studies. The list of selected articles was discussed between authors until consensus was achieved. All authors’ conflicts were discussed internally and resolved by a third author (FV). Quality assessment The methodological quality of the studies included in this review was evaluated by two independent reviewers (RM, FV) using a modified version of the Downs and Black checklist (Downs and Black, 1998 ). Out of 27 items, eleven items were identified as relevant by the authors which allows to evaluate overall reporting bias (items 1, 2, 3, 4, 6, 7, 10), and internal validity bias (items 16, 18, 20, 23) of the included studies. For this review, two items were replaced to ensure relevance for the investigated literature: item 4 (“Are the interventions of interest clearly described?”) was replaced by “Are the experimental conditions clearly described?”, and item 23 (“Were study subjects randomized to intervention groups?”) was replaced by “Were experimental conditions randomized for participants?”. The items were scored as 1 (“yes”), 0 (“no”), or UD (“Unable to Determine). The maximum total consists of 11 points per study. Each study was assigned a score of “high” (≥ 75%), “moderate” (60–74%), “low” (≤ 60%) (Desmyttere et al., 2018 ). When the quality scores differed among the reviewers, consensus was finally reached through discussion. Data extraction The details of each study were extracted by the author RM and were verified by two authors (CT or FV) in a table containing i ) general information (author names and year of publication, study design); ii ) methodological information (participant characteristics, study type, body segment studied, device used, experimental task, independent variables, and dependent variables); and iii ) main findings. Inter-rater agreement Cohen’s kappa was calculated to analyze inter-rater agreement for the overall study selection process. Kappa values 0.00–0.20 indicate poor, 0.21–0.40 fair, 0–41–0.60 moderate, 0.61–0.80 substantial, and greater than 0.81 almost perfect agreement. Results Search results The search yielded a total of 657 results. Following screening, 38 full-text articles were assessed for eligibility of which 23 were excluded. A total of 15 studies (including a total of 162 participants) were eligible for this review (Fig. 1). Inter-rater agreement for the overall study selection process yielded a Cohen’s kappa of 0.78, suggesting a substantial agreement between the two authors (RM and CT). Quality assessment The median quality score of the included studies was 82% (range from 55–100%) indicating a moderate to high quality (Table 2 ). Ten studies were of high quality (Dalla Bella & Palmer, 2011 ; Degrave et al., 2020 ; Furuya et al., 2010 , 2012 ; Goebl & Palmer, 2013 ; Goubault et al., 2021 ; Massie-Laberge et al., 2019 ; Thio-Pera et al., 2022 ; Verdugo et al., 2020; Wong et al., 2024), four studies were of moderate quality (Sforza et al., 2003; Shoda & Adachi, 2012 ; Thompson & Luck, 2012 ; Turner et al., 2022 ), and one study was of low methodological quality (Castellano et al., 2008 ). Table 2 Methodological quality assessment scores of included studies using the modified version of Downs and Black checklist. 1 = Yes; 0 = No; UD = Unable to Determine. Quality score: “High” (≥ 75%), “Moderate” (60–74%), “Low” (≤ 60%). Studies have been classified by the performance/abstract parameter manipulated. Q1: clear aim, Q2: clarity of reporting outcomes, Q3: clarity of participants' characteristics, Q4: clarity of experimental conditions, Q6: description of main findings, Q7: estimation and report of random variability, Q10: reporting actual probability values, Q16: clarity of probable data dredging, Q18: appropriate statistical tests, Q20: accuracy of outcome measures, Q23: randomization of experimental conditions. Music-expression related parameters Author & date Reporting Internal validity (bias) Score (%) Quality 1 2 3 4 6 7 10 16 18 20 23 Performance parameters Dalla Bella & Palmer, 2011 1 1 1 1 1 1 0 1 1 1 UD 82 High Degrave et al., 2020 1 1 1 1 1 1 1 1 1 1 UD 91 High Furuya et al., 2010 1 1 1 1 1 1 0 1 1 1 UD 82 High Furuya et al., 2012 1 1 1 1 1 1 0 1 1 1 1 91 High Goebl & Palmer, 2013 1 1 1 1 1 1 0 1 1 1 UD 82 High Goubault et al., 2021 1 1 1 1 1 1 1 1 1 1 1 100 High Sforza et al., 2003 0 1 1 1 1 1 1 1 1 0 UD 73 Moderate Thio-Pera et al., 2022 1 1 1 1 1 1 0 1 1 1 UD 82 High Turner et al., 2022 1 1 1 1 1 1 0 1 0 1 UD 73 Moderate Verdugo et al., 2020b 1 1 1 1 1 1 1 1 1 1 1 100 High Abstract parameters Castellano et al., 2008 1 1 0 0 1 1 0 1 1 0 UD 55 Low Shoda & Adachi, 2012 1 1 1 1 1 1 0 1 1 0 0 73 Moderate Thompson & Luck, 2012 1 1 1 1 1 1 0 1 1 0 UD 73 Moderate Massie-Laberge et al., 2019 1 1 1 1 1 1 1 1 1 0 1 91 High Performance and abstract parameters Wong et al., 2022 1 1 1 1 1 1 1 1 1 1 1 100 High Studies’ characteristics Out of the fifteen studies included, twelve were cross-sectional studies (Dalla Bella & Palmer, 2011 ; Degrave et al., 2020 ; Furuya et al., 2010 , 2012 ; Goebl & Palmer, 2013 ; Goubault et al., 2021 ; Massie-Laberge et al., 2019 ; Sforza et al., 2003; Thio-Pera et al., 2022 ; Thompson & Luck, 2012 ; Verdugo et al., 2020b ; Wong et al., 2022 ), and three were cross-sectional case studies (Castellano et al., 2008 ; Shoda & Adachi, 2012 ; Turner et al., 2022 ). Ten studies focused on the modification of performance parameters (Dalla Bella & Palmer, 2011 ; Degrave et al., 2020 ; Furuya et al., 2010 , 2012 ; Goebl & Palmer, 2013 ; Goubault et al., 2021 ; Sforza et al., 2003; Thio-Pera et al., 2022 ; Turner et al., 2022 ; Verdugo et al., 2020), four studies focused on the modification of abstract parameters (Castellano et al., 2008 ; Massie-Laberge et al., 2019 ; Shoda & Adachi, 2012 ; Thompson & Luck, 2012 ), and one study addressed both performance and abstract parameters (Wong et al., 2022 ). To enhance the readability and clarity of this systematic review, Table 3 , which summarizes the findings in each study, has been subdivided in three sections: Table 3 .A reports on studies investigating changes in performance parameters, Table 3 .B reports on studies investigating changes in abstract parameters, and Table 3 .C reports on the only study investigating changes in both performance and abstract parameters. The studies in Table 3 .A are classified by the performance parameter manipulated, and the studies in Table 3 .B are presented in chronological order. Table 3 A: Summary of studies included in the review that investigated the impact of changes in performance parameters on kinematics and/or muscle activity of pianists (the column ‘Main outcome’ summarizes one or maximum two main outcomes relevant for the present literature review). Author & date Participants Study Design Body segment studied Measurements Experimental task Independent variables Dependent variables Main outcome Sforza et al., 2003 N = 5 (3 males, 2 females) Professional pianists Cross-sectional study Right hand 3D motion capture system Digital piano A scale Three tempi: 80, 112 and 160 bpm Overlapping coefficients between trajectories for all fingers Repeatability of finger movements was lower in concert pianists than in teachers and learners Dalla Bella & Palmer, 2011 N = 4 (1 male, 3 females) 16.3 years of piano performing experience Cross-sectional study Right hand 3D motion capture system Digital piano Two melodies Five tempi: 60, 180, 210, 240, 250 bpm Mean movement amplitude (mm) and mean anticipation time (ms) of peak height for fingers Mean finger velocity (m/s) and mean acceleration (m/s²) MIDI data Peak finger heights preceding keystrokes and key velocity increased as tempo increased Goebl & Palmer, 2013 N = 12 At least 10 years of piano instruction Cross-sectional study Right fingers, hand, and wrist 3D motion capture system Digital piano A melody Ten tempi: 7.0, 8.4, 9.6, 10.7, 11.7, 12.3, 13.3, 14.1, 15.0, and 16.0 tones per second Joint angle trajectories for all adjacent finger phalanges, the hand, and the wrist Each finger joint did not change its relative contributions to the fingertip movements across tempi Turner et al., 2022 N = 3 (2 professionals and 1 intermediate-level with 11 years of piano study) Case Study Trunk and right hand 3D motion capture system Grand piano An excerpt Three tempi: 6, 8, and 10 notes/s (N/s) Starting position Initiation intervals Trunk range of motion (ROM) Right hand velocity (m/s) Right limb coordination As tempi increased, trunk and right-hand medio-lateral shifts were more synchronized Furuya et al., 2012 N = 18 (5 males, 13 females) More than 15 years of classical music Cross-sectional study Right upper limb (Finger, wrist, elbow, and shoulder joints) 6 Right upper-limb muscles (anterior and posterior deltoid (AD and PD), triceps brachii, biceps brachii, flexor digitorum superficialis (FDS), and extensor digitorum communis (EDC) 2D motion capture system (sagittal plane) EMG Upright piano Repetitive chord keystrokes Four loudness levels: piano (p), mezzo-piano (mp), mezzo-forte (mf), and forte (f) Four tempi: 180, 240, 300, and 360 bpm Peak angular velocity (rad/s) of the shoulder, elbow, wrist, and finger Mean muscle activation (%MVC) Interaction effect of loudness and tempo on peak angular velocity for all joints except for the elbow, and on muscular activity for all muscles Furuya et al., 2010 N = 7 (3 males, 4 females) More than 15 years of classical-piano training Cross-sectional study Right upper limb (upper arm, forearm, hand, and finger) 2D motion capture system (sagittal plane) Upright piano Repetitive isolated keystrokes Two loudness levels: piano (p) and forte (f) Pressed and struck touches Mean of joint angles (rad), fingertip and key's (mm) vertical position and velocities (rad/s, mm/s) Mean peak angular velocities (rad/s) Net joint acceleration (rad/s²) The pressed and struck touches effectively took advantage of the distal-to-proximal and proximal-to-distal inter-segmental dynamics, respectively Verdugo et al., 2020b N = 9 (7 males, 2 females) Holding or currently pursuing a doctoral degree in piano performance Cross-sectional study Pelvis, thorax, right upper limb and left lower limb 3D motion capture system Grand piano Repetitive isolated keystrokes Eight combinations of these three variables: 1) Body implication (use of trunk and upper-limb motion) or use of only upper-limb motion 2) Touch (pressed or struck) 3) Articulation (staccato or tenuto) Upper-limb linear velocities (m/s) Joint angular contribution (m/s) All upper-limb segments presented forward velocities during the key descent regardless of touch and articulation. Pelvic anterior rotation effectively contributed to creating forward linear velocities at the upper limb Degrave et al., 2020 N = 12 (10 males, 2 females) Professional pianists Cross-sectional study 9 Right upper-limb muscles (flexor digitorum superficialis, extensor digitorum communis, biceps brachii, triceps brachii, anterior deltoid, middle deltoid, great pectoral, upper trapezius, serratus anterior) EMG wireless sensor system Grand piano Repetitive isolated keystrokes Four possible combinations of: two types of touch (pressed or struck) and articulation (staccato or tenuto) Time histories of mean muscle activation (%MVC) Compared to tenuto articulation, staccato articulation induced a higher muscle activity on shoulder muscles Goubault et al., 2021 N = 49 (30 males, 19 females) All participants had at least a university (or equivalent) degree or were enrolled in undergraduate or graduate studies in piano performance Cross-sectional study Forearm muscles (finger and wrist flexor and extensor muscles) 49 monopolar EMG electrodes Grand piano Digital and chord excerpts Digital and chord excerpt Fatigue Rate of perceived exertion EMG median frequency Finger/wrist extensor muscles showed greater signs of fatigue than finger/wrist flexor muscles Pianists showed extremely different levels of endurance. Muscle fatigue negatively affected key velocity and note-accuracy Thio-Pera et al., 2022 N = 8 (6 males, 2 females) Professional piano players Cross-sectional study Forearm muscles (hand and wrist muscles) 32 monopolar EMG electrodes Upright piano Octaves and three excerpts Octaves were played in four conditions and two tempi: Four conditions: spezzate, loading the forearm, the wrist, and the fingers segments, each at a time Two tempi: self-paced speed and as fast as possible EMG average map Depending on playing contexts, professional pianists consistently load specific finger/wrist muscles, whether performing octaves (extensor muscles) or classical excerpts (flexor muscles) Table 3 B: Summary of studies included in the review that investigated the impact of changes in abstract parameters on pianists’ kinematics. Author & date Participants Study Design Body segment studied Measurements Experimental task Independent variables Dependent variables Main outcome Castellano et al., 2008 N = 1 female Professional concert pianist Case Study Overall body movement Video cameras Grand piano An excerpt Five different expressive modes: personal, sad, allegro, serene, and over-expressive Quantity of motion of the upper body and the velocity of head movements Velocity of head movements was influenced by expressive modes Shoda & Adachi, 2012 N = 1 male Professional pianist (who studied the piano for 20 years) Case Study Overall body movement Video cameras Grand piano Two excerpts Three levels of expression: deadpan, artistic, and exaggerated Mean value of the movement amplitude (rad) Pianist’s range of movement in the artistic condition differed from the other two for a fast, energetic piece, whereas it only differed from the deadpan for a slow, romantic piece Thompson & Luck, 2012 N = 8 (3 males, 5 females) Between 10 and 20 years of piano-playing experience Cross-sectional study Upper body (hip, torso, neck, head, shoulders, elbows, wrists, middle fingers) 3D motion capture system Digital piano An excerpt Four expressive intentions: normal, deadpan, exaggerated, immobile Duration of the performance (sec) Cumulative distance travelled by markers (mm) Markers at the head and at the shoulder exhibited more movement per measure, compared to the fingers, wrists, and lower back, for the normal and the exaggerated conditions Massie-Laberge et al., 2019 N = 10 (4 males, 6 females) The participants were all graduate or post-graduate students Cross-sectional study Hands, elbows, shoulders, torso, head, and pelvis 3D motion capture system Digital piano Three excerpts Four expressive conditions: normal, deadpan, exaggerated, and immobile Overall duration of the performances Cumulative distance travelled by markers (mm) Head movement recurrence Head movements are important for communicating different expressive playing conditions and structural features (ascending movements, crescendo dynamics, and at the beginning of the melodic theme and its repetition) Table 3 C: Summary of the study included in the review that investigated the impact of changes in both performance and abstract parameters on pianists’ kinematics. Author & date Participants Study Design Body segment studied Measurements Experimental task Independent variables Dependent variables Main outcome Wong et al., 2022 N = 15 (3 males, 12 females) Completed Level 9 music training or majored in piano at university at the time or before the data collection Cross-sectional study Upper body (head, neck, trunk, sacrum, great trochanter, forearm) 3D motion capture system Digital piano A scale and an excerpt Three expressive conditions: deadpan (no variation in dynamics or tempo), projected (played as they normally would in a performance), exaggerated (exaggerate all expressive features: tempo, dynamics) Spine angles for each segment (deg) Spine joint angles showed an average posture closer to neutral 1) in the deadpan playing compared to projected and exaggerated conditions, and 2) in playing an excerpt, compared to playing a scale Impact of performance parameters on pianists’ kinematics Technical Melodic Exercises As tempo increased in technical melodic exercises, one study showed that mean movement vertical amplitude averaged across all fingers increased (from ~ 17 mm with a tempo of 60 beats per minute (bpm) to ~ 27 mm with a tempo of 250 bpm) and key velocity increased (from ~ 43 MIDI units with a tempo of 60 bpm to ~ 68 MIDI units with a tempo of 250 bpm; Dalla Bella & Palmer, 2011 ). Another study showed that finger joints did not change their relative contributions to the vertical fingertip movements across tempi; only the wrist vertical movement contributed slightly more to the fingertip motion at fast tempi than at slow tempi (from a wrist vertical efficiency score of ~ 0/1 with a tempo of 7 tones per second to a wrist vertical efficiency score of ~ 0.3/1 with a tempo of 15 tones per second; Goebl & Palmer, 2013 ). Isolated Keystrokes With an increase of tempo (from 180 bpm to 360 bpm and with a loudness of forte ) during isolated keystrokes, Furuya et al. ( 2012 ) showed that peak angular velocities increased at the shoulder (from ~ 0.3 to ~ 0.37 rad/s) and the wrist (form ~-1.8 to ~-2.1 rad/s), but decreased at the elbow (from ~-2.2 to ~-1.3 rad/s). As loudness increased (from piano to forte and with a tempo of 180 bpm), peak angular velocities increased at all joints (shoulder: from ~ 0.14 to ~ 0.3 rad/s, elbow: from ~-0.7 to ~-2.2 rad/s, wrist: from ~-1.2 to ~-1.8 rad/s, and finger joints: from ~-1.8 to ~-2.5 rad/s; Furuya et al., 2012 ). Verdugo et al. ( 2020b ) found that shoulder-girdle joints contribution to finger upward velocity was greater during staccato articulation compared to tenuto articulation (absolute difference = 0.207 m/s, percentage difference = 206%). These authors also showed that pianists produced systematically forward upper-limb velocities during isolated keystroke attack and key holding/release phases regardless of the choice of articulation and touch. Repertoire Excerpts and Mixed Tasks Wong et al. ( 2022 ) found that spine joint angles showed an average posture closer to neutral while playing an excerpt (head tilt of 3.2 ± 8.3° in projected playing), compared to playing a scale (head tilt of -4 ± 8.9°). One study showed that trunk and right-hand movement were more synchronized at faster tempi when playing an excerpt (Turner et al., 2022 ). Moreover, when averaging between the three musical sections, the shortest pianist (1.65 m) had the greatest trunk range of motion (276 mm), and the tallest pianist (1.90 m) had the smallest trunk range of motion (101 mm). Impact of abstract parameters on pianists’ kinematics Three out of five studies found that playing conditions with a higher level of expressiveness (e.g., deadpan compared to normal, normal compared to exaggerated) resulted in more head and proximal movements compared to deadpan condition (Castellano et al., 2008 ; Massie-Laberge et al., 2019 ; Thompson & Luck, 2012 ). For example, Thompson & Luck ( 2012 ) found that the distance travelled by the right and the left shoulder was between ~ 200 to ~ 300 mm per measure for the exaggerated conditions, and between ~ 10 to ~ 50 mm per measure in the deadpan condition. Similarly, Shoda & Adachi ( 2012 ) found that a pianist increased upper body movements in the artistic and exaggerated conditions compared to the deadpan condition. In addition, one study found that spine joint angles showed an average posture closer to neutral in the deadpan playing (craniovertebral angle of 43.5 ± 7.6°), compared to the other two conditions (craniovertebral angle of 38.3 ± 7.6° and 37.9 ± 9° for the projected and exaggerated conditions, respectively; Wong et al., 2022 ). Impact of performance parameters on pianists’ muscle activity Studies investigating muscle activity focused on isolated keystrokes and musical excerpts. Isolated Keystrokes Both the activation level of six muscles (anterior and posterior deltoids, biceps brachii, triceps brachii, flexor digitorum superficialis, and extensor digitorum communis) and the co-activation index between the anterior-posterior deltoid, biceps-triceps brachii, and flexor digitorum superficialis-extensor digitorum communis muscle pairs increased at a tempo of 5 keystrokes per second or higher (Furuya et al., 2012 ). As loudness increased (from p to mp , mp to mf , and mf to f ), the activation level of the above-mentioned muscles and their co-activation index increased (Furuya et al., 2012 ). The activation level particularly increased for distal muscles (the flexor digitorum superficialis, and the extensor digitorum communis increased their muscle activity from ~ 4–5% maximum voluntary contraction (MVC) at slow tempi, to ~ 10% MVC at faster tempi). During and after key descent and release, staccato articulation showed a higher activity in the shoulder muscles, compared to tenuto articulation (upper trapezius + 2.1% MVC, anterior deltoid + 2.5% MVC, great pectoralis + 3.8% MVC; Degrave et al., 2020 ). One study showed that professional pianists activated more finger/wrist extensor muscles than finger/wrist flexor muscles when performing octaves (Thio-Pera et al., 2022 ). Musical Excerpts Thio-Pera et al. ( 2022 ) showed that professional pianists activated more finger/wrist flexor muscles than finger/wrist extensor muscles when performing repertoire excerpts compared to octaves. Constant repetition of a digital exercise and a chord musical excerpt, both performed loud and fast, showed higher levels of muscle fatigue at finger/wrist extensor muscles (the EMG median frequency decreased between 10 and 20 Hz at task termination) compared to the respective flexors (the EMG median frequency decreased between 2 and 10 Hz), and pianists showed different levels of endurance in their time-to-task termination (from around 2 min to 12 min, which was the maximum time allowed for the task; Goubault et al., 2021 ). Ontological and methodological choices Ontological choices (focus of studies, gestural variable investigated) and methodological choices (kinematic and EMG data collection tools, experimental tasks, musical instrument used) are reported in Fig. 2. Regarding kinematic analysis, the gestural variables investigated were different between studies focusing on the modification of performance parameters and studies focusing on abstract parameters. Studies focusing on the modification of performance parameters assessed either i ) finger and/or wrist linear velocities (Dalla Bella & Palmer, 2011 ; Turner et al., 2022 ), joint angles (Goebl & Palmer, 2013 ), and movement repeatability (Sforza et al., 2003) ; and ii ) right upper limb (Furuya et al., 2010 , 2012 ) or upper body (Verdugo et al., 2020b ) linear and joint kinematics (e.g., joint angular velocities, segmental linear velocities, etc.). Studies focusing on abstract parameters measured either i ) the quantity of motion, (i.e., an approximation of the amount of detected movement, based on Silhouette Motion Images, which represent all variations of a simplified white-body silhouette, obtained using background subtraction; Castellano et al., 2008 ), and the cumulative distance travelled by markers (Massie-Laberge et al., 2019 ; Thompson & Luck, 2012 ); or ii ) postural angles of the spine (Shoda & Adachi, 2012 ; Wong et al., 2022 ). Regarding EMG analysis, two studies calculated mean muscle activation over the entire trial (Furuya et al., 2012 ; Thio-Pera et al., 2022 ), one study calculated time series muscle activation (Degrave et al., 2020 ), and one study calculated the EMG median frequency to assess the myoelectric manifestation of muscle fatigue (Goubault et al., 2021 ). Risk factors of playing-related musculoskeletal disorders A complementary objective was to address how music expression affects pianists’ exposure to risk factors of PRMDs. Risk factors of PRMDs associated with music expression could only be extracted from the studies focusing on performance parameters. The type of task, playing factor, and biomechanical impact addressed by these studies are summarized in Table 4 . Four playing factors have been identified as potential risk factors of PRMDs: playing loud, playing fast, staccato articulation, and large handspan chords (Table 4 ). Table 4 Type of tasks, playing factors, and biomechanical impacts of included studies. Author & date Type of task Playing factor Biomechanical impact Dalla Bella & Palmer, 2011 Melodic exercise Playing fast Increase in fingertip height Degrave et al., 2020 Isolated keystrokes Staccato articulation Increase in shoulder muscle activation Furuya et al., 2012 Isolated keystrokes Playing loud and fast Increase in muscle activation of six upper limb muscles (anterior and posterior deltoids, biceps brachii, triceps brachii, flexor digitorum superficialis, and extensor digitorum communis) Goubault et al., 2021 Repetitive melodic and chord tasks Playing loud and fast Increase in finger/wrist extrinsic extensor muscle fatigue Thio-Pera et al., 2022 Consecutive octaves Large handspan chords Increase in finger/wrist extensor muscle activity Discussion This systematic review investigated how both performance and abstract parameters of music expression impact pianists’ gestures. It also addressed ontological and methodological differences of the included studies and the impact of music expression-related parameters on exposure to risk factors of PRMDs. Fifteen studies were included. Ten studies focused on the modification of performance parameters (i.e., sound intensity, tempo, articulation), four studies focused on the modification of abstract parameters (structural and/or semantic), and one study focused on both. Performance and abstract parameters impacted pianists’ kinematics and muscle activity, the specific effects being dependent on the type of task (i.e., isolated tones, digital task, chord task) and the gestural variable investigated by studies. Important differences in ontological (performance or abstract parameters studied, gestural variable investigated) and methodological choices (experimental task and instrument used, data acquisition and processing procedures) prevent the establishment of a thorough dialogue between studies focusing on performance and abstract parameters. Risk factors of PRMDs associated with music expression parameters included playing loud, playing fast, staccato articulation, and playing large handspan chords. Impact of music expression on pianists’ gestures Loudness and articulation In isolated keystrokes, loudness and articulation had clear and consistent effects across studies. An increase in loudness led to greater angular velocities and muscle activity at both distal and proximal joints/segments of the right upper limb (Furuya et al., 2012 ). These results are consistent with piano sound-production mechanics, as loudness is closely related to the key attack velocity (e.g., Dannenberg, 2006 ). To increase the targeted key velocity of louder tones, pianists increased velocity and muscle activity at upper-limb joints (shoulder, elbow, wrist). Articulation had a similar effect, but in relation to the release motion. Staccato articulation (in opposition to tenuto articulation) increased upper-limb upward/forward velocities (Verdugo et al., 2022 ) and shoulder muscle activity (Degrave et al., 2020 ) during and after the key descent in the context of isolated keystrokes, as the shoulder-girdle joints were the primary mover of the rapid lifting motion of the arm and hand after the attack (Verdugo et al., 2022 ). In brief, the production of faster key attack (louder tones) and key release ( staccato tones) movements demands an increased velocity and muscle activity at the joints responsible for those faster endpoint movements. These studies have been conducted on simple performance tasks (repetitive isolated keystrokes). However, in more complex musical contexts, it seems possible to hypothesize that the same relation may prevail (i.e., increase of joint velocity and muscle activity allowing faster key attack and release movements). Tempo In the case of technical melodic exercises, an increase in tempo led to an increase in the height of the fingers before the keystroke (Dalla Bella & Palmer, 2011 ). The most important finger joint to produce the fingertip vertical movement during this type of melodic exercises was the metacarpophalangeal joint, and its contribution remained stable across different tempi (Goebl & Palmer, 2013 ). These results point to two ideas. First, faster tempi impose spatiotemporal constraints that require an increased distance between the fingertip and the key before the attack to produce the targeted key attack velocity. Second, this increased height of the fingertip might increase the extension motion of the metacarpophalangeal joint. Furuya et al. ( 2011 ) showed that during fast alternate keystrokes (i.e., tremolo), expert pianists used hand pronation/supination (a degree of freedom at the elbow) to reduce metacarpophalangeal muscle load. As pianists can use pronation/supination not only during alternate keystrokes but also during a wide range of melodic passages (scales, arpeggios, etc.), the increased finger height at faster tempi reported by Dalla Bella & Palmer ( 2011 ) could be achieved by multi-joint hand/forearm movements rather than by isolated metacarpophalangeal joint movements. Dalla Bella & Palmer ( 2011 ) did not address interactions of loudness and tempo in their study. However, as louder sounds entail faster joint and key velocities, the required finger height needed to play at a certain tempo might also be affected by the targeted sound intensity. This must nevertheless be confirmed by future research. During repetitive isolated keystrokes, varying the tempo produced distinct effects on peak angular velocities at different joints. Despite the interactions between loudness and tempo reported in Furuya et al. ( 2012 ), these authors observed that an increase in tempo resulted in faster peak flexion/extension velocities at the shoulder and wrist and slower peak velocities at the elbow. Similarly, two recent studies showed a reduction of elbow flexion/extension range of motion while playing repetitive chords at faster tempi (Turner et al., 2023 ; Wang et al., 2023 ). If elbow extension was the main contributor of the fingertip downward attack velocity during slow isolated keystrokes (Verdugo et al., 2020b ), the results of the above-mentioned studies show that the leading role of the elbow to produce the attack downward velocity of the fingertip decreases while tempo increases. However, this tempo-dependent change of inter-joint coordination did not imply a reduction of elbow muscle activity, as faster tempi produced greater mean muscle activity at proximal and distal joints of the upper limb and higher co-contraction levels of elbow and finger muscles (Furuya et al., 2012 ). Type of task Thio-Pera et al. ( 2022 ) found different task-dependent finger/wrist muscle loads regardless of tempo, where consecutive octaves induced greater activations at extrinsic extensors while other types of excerpts (melodic ‘finger’ passage, slow-loud chord passage) induced greater activations at extrinsic flexors. To play consecutive octaves, pianists constantly hold the hand in a fixed position characterized by finger extension/abduction (which is coherent with the increased activity of extrinsic extensors reported by the authors). This is not the case in the other excerpts used in Thio-Pera et al. ( 2022 ), as distal joint posture and movements can be adapted at each keystroke or group of keystrokes. Chong et al. ( 2015 ) also found that muscle activation in hand extrinsic muscles was dependent on the configuration of the notes imposed in the score. However, Goubault et al. ( 2021 ) found higher levels of fatigue at finger/wrist extrinsic extensor muscles (compared to flexors) regardless of the type of task. Extensor muscles showed higher signs of fatigue during both a chord passage (involving octaves) and a melodic ‘finger’ passage played repetitively in cycles. These results suggest that even though muscle load is dependent on note configuration (i.e., task dependent muscle load), muscle fatigue might greatly affect specific muscles due to their intrinsic characteristics or the duration of the repetitive activations. Abstract parameters and gestural functions Regarding abstract parameters, Thompson & Luck ( 2012 ) and Massie-Laberge et al. ( 2019 ) found that playing conditions with a higher level of expressiveness (e.g., deadpan compared to normal, normal compared to exaggerated) resulted in more movement at markers placed on the head and proximal segments. These findings underline the role of performers’ whole-body movements as a tool to encode or embody the expressive content of music while playing (Krumhansl, 2002 ; Leman & Maes, 2015 ). These gestures have been associated with sound-facilitating gestures (or ancillary gestures) by the cited studies and the related literature (Massie-Laberge et al., 2019 ; Thompson & Luck, 2012 ; Wanderley et al., 2005 ). However, delimitation of what body movements are labelled as sound-facilitating and as sound-producing is not clearly addressed. Typically, in this literature, sound-facilitating gestures involve the trunk and the head, while sound-producing gestures involve distal segments close to the performer-instrument interface (forearm, hand, fingers; Jensenius et al., 2010 ). Thus, these two types of gestures are usually understood as distinct gestures and have been studied separately in the literature. However, Verdugo et al. ( 2020b ) showed that pianists’ pelvis and thorax movements can play a role in the control of performance parameters related to articulation and loudness. Moreover, other recent studies have also highlighted the role of trunk motion in pianists’ sound-production strategies (Turner et al., 2022 , 2023 ; Verdugo et al., 2022 ). In the case of piano performance, it therefore seems clear that sound-producing and sound-facilitating gestures are not distinct gestures but are rather gestural functions embedded in the same gestural space incorporating the entire kinematic chain (pelvis, thorax, upper limbs, and potentially lower limbs). To enhance dialogue and coherence between the literature addressing the impact of performance and abstract parameters on pianists’ gestures, we recommend a more systematic use of the concepts of sound-producing and sound-facilitating gestural functions , rather than sound-producing and sound-facilitating gestures . Ontological and methodological differences of the targeted literature One of the main ontological differences of the studies in this review relates to the type of music expression-related parameters investigated. The ten studies addressing performance parameters focused on ‘score-imposed’ variations of performance parameters. For example, playing the same task at the piano with different imposed tempi (e.g., Sforza et al., 2003), different articulation (e.g., Degrave et al., 2020 ), and different loudness levels (e.g., Furuya et al., 2012 ). In addition, these studies, generally from the field of biomechanics and motor control, did not consider abstract parameters (music structure parameters and extra-musical or semantic ideas) from research questions. On the contrary, studies from the music research domain addressing abstract parameters investigated the effect of music expression on pianists’ gestures in relation to the performers’ interpretation of the score. By using notions such as expressive intentions and experimental conditions based on different levels of expression (deadpan, normal, exaggerated), these studies addressed music expression from the performers’ point of view. This different focus on expression (score-imposed features versus performers’ interpretation features) is a key difference that hampers the establishment of a connection between research on musicians’ gestures from biomechanics and motor control, on one hand, and from music research and empirical musicology, on the other hand. Biomechanical studies addressing the impact of pianists’ personal management of abstract parameters would be necessary to strengthen the link between literature from biomechanics and music research, and enable a deeper understanding of the impact of music expression (linked to the creative work not only of the composer but also of the performer) on pianists’ gestures. A key methodological difference in studies focusing on pianists’ kinematics relates to the choice of the kinematic variable investigated. It is noteworthy that most studies (eight out of twelve focusing on pianist’s kinematics) used 3D motion capture systems (Fig. 2). Despite one exception (Wong et al., 2022 ), studies on pianists’ sound-facilitating gestures analyzed segmental kinematics based on data of markers placed on the body (e.g., quantity of motion, distance travelled by markers), with little or no attention to joint kinematics or more thorough methods for the computation of segmental kinematics (using for example segment endpoint or center of mass). Therefore, studies in music research do not usually take advantage of methods from biomechanics to analyze and address the interdependent nature of movements of multi-body systems such as the human body. An interdisciplinary approach mixing methods from empirical musicology and biomechanics would, first, facilitate a better understanding of the interrelated nature of sound-producing and sound-facilitating functions in the context of multi-joint movements of pianists. Second, as abstract parameters might not only affect pianists’ kinematics but also muscle activity (Verdugo et al., 2020a , 2022 ), this interdisciplinary approach would allow to assess the impact of pianists’ expressive intentions on their muscle load, with implications for both embodied cognition and injury prevention research. As an example, in a recent case study on two participants, Mailly et al., 2024 showed that pianists can embody their expressive intentions in different musical contexts through upper-body muscle activity, including proximal (upper trapezius, external oblique,) and distal muscles, such as flexor digitorum superficialis and extensor digitorum communis. Another important methodological difference was associated with the instrument used. Six studies used a grand piano, six studies used a digital piano, and three studies used an upright piano (Fig. 2). Acquiring pianists’ movements using optoelectronic cameras and passive markers remains a challenge due to marker occlusions caused by the piano itself. Despite this obstacle, several studies have been conducted with grand piano using these motion capture systems (Turner et al., 2021 , 2022 ; Verdugo et al., 2020b , 2022 ). The grand piano is the actual instrument where pianists usually perform and practice and its specific key action mechanism influences pianists’ touch and sound control (Traube et al., 2017 ). Therefore, the use of digital instruments to facilitate motion capture procedures may change how pianists manipulate both performance and abstract music expression-related parameters, and consequently, influence research results. This methodological limitation was highlighted in a previous literature review on piano touch (MacRitchie, 2015 ). However, it remains relevant for the current state of the literature. Risk factors of PRMDs and considerations for injury prevention The following four playing factors were associated with increased muscle load or muscle fatigue: playing loud, playing fast, staccato articulation, and playing large handspan chords. The included studies in this review did not address the relationship between the reported increase of muscle activation or fatigue and PRMDs history in the participants recruited. Nevertheless, increases in muscle load and muscle fatigue are typically considered prominent risk factors of musculoskeletal disorders in music (Ling et al., 2018 ), sports, and daily life activities (Côté, 2014 ). In addition, questionnaire-based studies have shown that large handspan chords (such as octaves; Allsop, 2007 ; Sakai, 2002 ; Shields & Dockrell, 2000 ), and playing chords loudly (Furuya et al., 2006 ) were associated to the development of PRMDs. In this direction, future studies should investigate gestural strategies that can reduce exposure to the four above-listed risk factors. Moreover, considering that these playing factors are extremely common in the piano repertoire, quantification of practice load based on these playing factors might also help reduce occurrence of pianists’ PRMDs. Recent studies in sport science literature focusing on injury prevention (e.g., running, tennis) have centered on the concept of ‘training load’ (Coutts et al., 2011 ; Drew & Finch, 2016 ; Gabbett, 2016 ). Training load is quantified by multiplying the duration of each training session by its intensity, usually assessed using the perception of effort on a scale of 1 to 10 (Foster et al., 1996 ). Subsequently, the evolution of the training load is assessed on a weekly basis. Literature has shown that when training load increases by more than 15% above the previous week training load, prevalence of injury increases by 21–49% (Gabbett, 2016 ). Therefore, it has been concluded that to minimize the risk of injuries in athletes, it is advisable to maintain training load weekly increases below 10%. While the concept of playing load has recently been studied in relation to music performance (McCrary et al., 2022 ), monitoring playing load based on the playing factors identified in this review as a prevention strategy of PRMDs has yet to be studied. Therefore, future studies could develop playing load models to both quantify playing load and its fluctuation and predict occurrence of PRMDs in pianists, especially during the preparation process of upcoming performances or music competitions. Limitations Limitations of this systematic review include search strategy and methodological differences between studies. First, limitations in database coverage may have resulted in some relevant studies being overlooked. However, the search strategy was performed in 4 databases, which improved coverage, and decreased the risk of making inappropriate conclusions (Ewald et al., 2022 ). Second, the included studies differed in their design (cross-sectional studies or case studies). The studies also varied in their focus, addressing different parameters (performance or abstract parameters, or both), type of tasks (i.e., isolated tones, digital task, chord task, musical excerpts) and gestural variables investigated (linear segmental kinematics, joint angles, muscle activity), which limited the comparison between studies. However, most of the included studies showed a moderate to high methodological quality assessment score, suggesting that the overall quality of the results was not compromised. Conclusion This systematic review investigated how both performance parameters (timing, sound intensity, articulation) and abstract parameters (related to music structure and extra-musical or semantic content) of music expression impact pianists’ gestures. We also addressed ontological and methodological differences, and how music expression-related parameters affected pianists’ exposure to risk factors of PRMDs. Performance and abstract parameters impacted pianists’ kinematics and muscle activity, the specific effects being dependent on the type of task and the gestural variable investigated by studies. Important differences in ontological (performance or abstract parameters studied, gestural variable investigated) and methodological choices (experimental task and instrument used, data acquisition and processing procedures) prevent the establishment of a thorough dialogue between studies focusing on performance and abstract parameters. Four playing factors (playing loud, playing fast, staccato articulation, and large handspan chords) were identified as potential risk factors of PRMDs. To enhance the dialogue and coherence between the literature addressing the impact of performance and abstract parameters on pianists’ gestures, two avenues can be proposed. First, the use of a more precise terminology to designate the pianists' gestures. As sound-producing and sound-facilitating gestures are embedded in the same gestural space, a more systematic use of the concepts of sound-producing and sound-facilitating gestural functions is recommended, rather than sound-producing and sound-facilitating gestures . Second, a multidisciplinary approach may be needed to bridge the gap between studies from empirical music research and biomechanics. In this direction, future studies in empirical music research could make use of joint kinematics and muscle activity analysis used in biomechanics. Similarly, future studies in biomechanics and motor control could focus on the abstract parameters of musical expression. This could help develop a more comprehensive knowledge on the impact of music expression on pianists’ gestures for both performance and injury prevention purposes. Declarations Funding This work was supported by the Social Science and Humanities Research Council of Canada (Insight Development Grant 430-2021-00384). Acknowledgments We would like to thank Denis Arvisais (librarian at University of Montreal) for his help in the creation and execution of the search strategy. Competing interests The authors have no conflict of interest to report. Ethical approval This research did not require ethics committee or IRB approval. This research did not involve the use of personal data, fieldwork, or experiments involving human or animal participants, or work with children, vulnerable individuals, or clinical populations. 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Journées d'Informatique Musicale, May 2024, Marseille, France. ⟨hal-04661288v1⟩ Massie-Laberge, C., Cossette, I., & Wanderley, M. M. (2019). Kinematic Analysis of Pianists’ Expressive Performances of Romantic Excerpts: Applications for Enhanced Pedagogical Approaches. Frontiers in Psychology, 9, 2725. https://doi.org/10.3389/fpsyg.2018.02725 McCrary, J. M., Ascenso, S., Savvidou, P., Schraft, S., McAllister, L., Redding, E., Bastepe-Gray, S., & Altenmüller, E. (2022). Load and fatigue monitoring in musicians using an online app: A pilot study. Frontiers in Psychology, 13, 1056892. https://doi.org/10.3389/fpsyg.2022.1056892 Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, n71. https://doi.org/10.1136/bmj.n71 Palmer, C. (1996). On the Assignment of Structure in Music Performance. Music Perception, 14(1), 23–56. https://doi.org/10.2307/40285708 Repp, B. H. (1995). Acoustics, perception, and production of legato articulation on a digital piano. The Journal of the Acoustical Society of America, 97(6), 3862–3874. https://doi.org/10.1121/1.413065 Repp, B. H. (1998). A microcosm of musical expression. I. Quantitative analysis of pianists’ timing in the initial measures of Chopin’s Etude in E major. The Journal of the Acoustical Society of America, 104(2), 1085–1100. https://doi.org/10.1121/1.423325 Sakai, N. (2002). Hand Pain Attributed to Overuse among Professional Pianists: A Study of 200 Cases. Medical Problems of Performing Artists, 17(4), 178–180. https://doi.org/10.21091/mppa.2002.4028 Sforza, Turci, Michela, & Marci, Chiara. (2003). Neuromuscular patterns of finger movements during piano playing. Definition of an experimental protocol. Italian Journal of Anatomy and Embryology, 108(4), 211–222. Shields, N., & Dockrell, S. (2000). The Prevalence of Injuries among Pianists in Music Schools in Ireland. Medical Problems of Performing Artists, 15(4), 155–160. https://doi.org/10.21091/mppa.2000.4030 Shoda, H., & Adachi, M. (2012). The Role of a Pianist’s Affective and Structural Interpretations in his Expressive Body Movement: A Single Case Study. Music Perception, 29(3), 237–254. https://doi.org/10.1525/mp.2012.29.3.237 Thio-Pera, A., De Carlo, M., Manzoni, A., D’Elia, F., Cerone, G. L., Putame, G., Terzini, M., Gazzoni, M., Bignardi, C., & Vieira, T. (2022). Are the forearm muscles excited equally in different, professional piano players? PLOS ONE, 17(3), e0265575. https://doi.org/10.1371/journal.pone.0265575 Thompson, M. R., & Luck, G. (2012). Exploring relationships between pianists’ body movements, their expressive intentions, and structural elements of the music. Musicae Scientiae, 16(1), 19–40. https://doi.org/10.1177/1029864911423457 Traube, C., Moulin, M., & Verdugo, F. (2017). Controlling piano tone by varying the « weight » applied on the key. The Journal of the Acoustical Society of America, 141(5), 3874–3874. https://doi.org/10.1121/1.4988663 Turner, C., Goubault, E., Maso, F. D., Begon, M., & Verdugo, F. (2023). The influence of proximal motor strategies on pianists’ upper-limb movement variability. Human Movement Science, 90, 103110. https://doi.org/10.1016/j.humov.2023.103110 Turner, C., Visentin, P., Oye, D., Rathwell, S., & Shan, G. (2022). An Examination of Trunk and Right-Hand Coordination in Piano Performance: A Case Comparison of Three Pianists. Frontiers in Psychology, 13, 838554. https://doi.org/10.3389/fpsyg.2022.838554 Turner, C., Visentin, P., Shan, G., & Turner, vin. (2021). Wrist Internal Loading and Tempo-Dependent, Effort-Reducing Motor Behaviour Strategies for Two Elite Pianists. Medical Problems of Performing Artists, 36(3), 141–149. https://doi.org/10.21091/mppa.2021.3017 Verdugo, F., Begon, M., Gibet, S., & Wanderley, M. M. (2022). Proximal-to-Distal Sequences of Attack and Release Movements of Expert Pianists during Pressed-Staccato Keystrokes. Journal of Motor Behavior, 54(3), 316–326. https://doi.org/10.1080/00222895.2021.1962237 Verdugo, F., Ceglia, A., Frisson, C., Burton, A., Begon, M., Gibet, S., & Wanderley, M. M. (2022). Feeling the Effort of Classical Musicians—A Pipeline from Electromyography to Smartphone Vibration for Live Music Performance. NIME 2022. NIME 2022, The University of Auckland, New Zealand. https://doi.org/10.21428/92fbeb44.3ce22588 Verdugo, F., Kokubu, S., Wang, J., & Wanderley, M. M. (2020a). MappEMG: Supporting Musical Expression with Vibrotactile Feedback by Capturing Gestural Features through Electromyography. Verdugo, F., Pelletier, J., Michaud, B., Traube, C., & Begon, M. (2020b). Effects of Trunk Motion, Touch, and Articulation on Upper-Limb Velocities and on Joint Contribution to Endpoint Velocities During the Production of Loud Piano Tones. Frontiers in Psychology, 11, 1159. https://doi.org/10.3389/fpsyg.2020.01159 Vines, B. W., Krumhansl, C. L., Wanderley, M. M., & Levitin, D. J. (2006). Cross-modal interactions in the perception of musical performance. Cognition, 101(1), 80–113. https://doi.org/10.1016/j.cognition.2005.09.003 Wanderley, M. M., & Depalle, P. (2004). Gestural Control of Sound Synthesis. Proceedings of the IEEE, 92(4), 632–644. https://doi.org/10.1109/JPROC.2004.825882 Wanderley, M. M., Vines, B. W., Middleton, N., McKay, C., & Hatch, W. (2005). The Musical Significance of Clarinetists’ Ancillary Gestures: An Exploration of the Field. Journal of New Music Research, 34(1), 97–113. https://doi.org/10.1080/09298210500124208 Wang, H., Nonaka, T., Abdulali, A., & Iida, F. (2023). Coordinating upper limbs for octave playing on the piano via neuro-musculoskeletal modeling. Bioinspiration & Biomimetics, 18(6), 066009. https://doi.org/10.1088/1748-3190/acfa51 Wong, G. K., Comeau, G., Russell, D., & Huta, V. (2022). Postural Variability in Piano Performance. Music & Science, 5, 205920432211378. https://doi.org/10.1177/20592043221137887 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Published Journal Publication published 26 Feb, 2025 Read the published version in Music & Science → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5204526","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":362333682,"identity":"53090caa-b92f-4f4a-ad6e-6c0deb8414ef","order_by":0,"name":"Robin Mailly","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYFACHoYDIIqNnbmB4QNctIAYLcyMDYwzwCwQYYBfCwQAtTDzEKPFvL334OEChm3yfMyMbdK2bdvkzOV7Hz74YcAgz9+AXYvMmXMJh2cw3DZsA2nJbbttbNnGbmzYY8BgOOMAdi0SEjkGh3kYbjPCtCRuOMbGJsFjwJDAQECLPViLJUQL+88/QC3yBLQkgrUwQm1hBtligEsLD9AvPAa3k4Fami17zt02NjiWxiwtYyBhuBGXFvbew595Km7bzm9vPnjjR9ltOYPDxxg/vqmwkZfDoQUCILHAIoFsFj71cMD8gbCaUTAKRsEoGIkAAEpIUwklFOo1AAAAAElFTkSuQmCC","orcid":"","institution":"Université de Montréal","correspondingAuthor":true,"prefix":"","firstName":"Robin","middleName":"","lastName":"Mailly","suffix":""},{"id":362333683,"identity":"b9d84c83-0855-4f93-a803-2b0d88a3cde7","order_by":1,"name":"Craig Turner","email":"","orcid":"","institution":"Université de Montréal","correspondingAuthor":false,"prefix":"","firstName":"Craig","middleName":"","lastName":"Turner","suffix":""},{"id":362333684,"identity":"7d8b7d9c-e7e4-4c2f-9dc8-029e11474d73","order_by":2,"name":"Etienne Goubault","email":"","orcid":"","institution":"Université de Montréal","correspondingAuthor":false,"prefix":"","firstName":"Etienne","middleName":"","lastName":"Goubault","suffix":""},{"id":362333685,"identity":"cab10bcf-ca59-42e8-a222-f0d12840afaa","order_by":3,"name":"Fabien Dal Maso","email":"","orcid":"","institution":"Université de Montréal","correspondingAuthor":false,"prefix":"","firstName":"Fabien","middleName":"Dal","lastName":"Maso","suffix":""},{"id":362333686,"identity":"0af05da1-6366-497c-943e-15600bf80397","order_by":4,"name":"Felipe Verdugo","email":"","orcid":"","institution":"Université de Montréal","correspondingAuthor":false,"prefix":"","firstName":"Felipe","middleName":"","lastName":"Verdugo","suffix":""}],"badges":[],"createdAt":"2024-10-04 14:11:24","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5204526/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5204526/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1177/20592043251317019","type":"published","date":"2025-02-27T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":66168833,"identity":"218e697d-8dab-482c-8a3d-2b1e970a3556","added_by":"auto","created_at":"2024-10-08 10:20:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":275490,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA diagram of the study screening process and article selection.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-5204526/v1/4a7692e91e8e38d2bc0b08f5.png"},{"id":66168271,"identity":"aaf3b4b7-82f0-417e-8d63-2cc9e3d10c8f","added_by":"auto","created_at":"2024-10-08 10:12:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":335262,"visible":true,"origin":"","legend":"\u003cp\u003eOverview of the included studies. Distribution of A) Focus of studies, B) Gestural variable investigated, C) Kinematic and EMG data collection tools, D) Experimental tasks, and E) Musical instrument used. Definition of experimental tasks: isolated keystrokes (isolated notes or octaves), technical melodic exercise (scale or arpeggio type of tasks), repertoire excerpts (actual excerpts from the repertoire), mixed tasks (studies using both repertoire and other types of tasks). Other: analysis of head movements and other body segments using 2D videos of performances.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-5204526/v1/e84d3b414569d1d8fb093347.png"},{"id":77633225,"identity":"e1f7b36b-0b41-410e-b345-26fc8ef87845","added_by":"auto","created_at":"2025-03-03 17:55:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2155342,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5204526/v1/0adab341-fb8b-466e-9d86-37c99f756c76.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eImpact of Music Expression-Related Parameters on Pianists’ Kinematics and Muscle Activity: A Systematic Review\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn music research, musicians\u0026rsquo; body movements are usually characterized as gestures. The notion of gesture encompasses both the physical movement and its mental or cognitive aspects (e.g., expression of an idea or meaning; Jensenius et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Analyzing pianists\u0026rsquo; gestures is complex, as a great variety of multi-joint kinematic strategies and muscular activities can be used to produce a single piano tone (Furuya \u0026amp; Altenm\u0026uuml;ller, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Moreover, the literature suggests that amateur and expert pianists show different movement strategies and muscle recruitment while playing similar tasks (Furuya et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Furuya \u0026amp; Kinoshita, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Musicians\u0026rsquo; gestures during performance have been classified according to their function. Four functional categories of musical gestures have been reported in the literature: sound-producing gestures, sound-facilitating gestures, communicative gestures, and sound-accompanying gestures (Dahl et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Jensenius et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Sound-producing gestures are responsible for the effective production of sound (e.g., the striking of a piano key). Sound-facilitating gestures usually refer to bodily movements used to support sound-producing gestures for different music expression needs (e.g., the coordinated movements of musicians\u0026rsquo; arms and trunk to shape the musical phrasing of the performance). These gestures are also called ancillary gestures in the relevant literature (Wanderley \u0026amp; Depalle, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Communicative gestures are intended for communication with another performer and/or with the audience. Finally, sound-accompanying gestures are made in response to the music. Sound-producing and sound-facilitating gestures have been the primary object of study in the experimental research focusing on musicians\u0026rsquo; gestures. These two gestural functions have been typically associated to different music expression-related parameters.\u003c/p\u003e \u003cp\u003eMusic expression is a complex concept encompassing different phenomena and can be studied from a variety of disciplines (music theory, musicology, semiotic, semantics, psychology, neurosciences, performance science, biomechanics, among others). From pianists\u0026rsquo; perspective, music expression-related parameters can be grouped in at least two main categories. First, performance parameters such as rhythm and timing (related to timing management at both micro and macro levels of a musical piece; Repp, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), sound intensity (Drake \u0026amp; Palmer, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1993\u003c/span\u003e), and articulation (Repp, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). This type of parameters are often called performance parameters because they are sound features effectively manipulated by pianists during practice and performance (i.e., piano tones can be louder/softer, longer/shorter, and time between tones can be longer/shorter). While performance parameters are defined (at a certain extent) by the composer in the musical score, pianists shape their performance of musical pieces by modulating these parameters according to their personal interpretation of the score (Bernays \u0026amp; Traube, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Canazza et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Palmer, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Repp, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Pianists\u0026rsquo; sound-producing gestures are generally associated with the effective control of performance parameters and have been investigated by research focusing on music biomechanics and motor control (Furuya \u0026amp; Altenm\u0026uuml;ller, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Goebl, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The main goal of this body of literature is to assess if the manipulation of performance parameters may have an impact on exposure to risk factors of playing-related musculoskeletal disorders (PRMDs) (e.g., Degrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Furuya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Turner et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This is an important topic for musicians, as lifetime prevalence of PRMDs ranges between 62% and 93% among professional instrumentalists (Kok et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, no study has yet synthesised the current findings on the impact of performance parameters on pianists\u0026rsquo; kinematics and muscle activity.\u003c/p\u003e \u003cp\u003eMusic performance implies not only the effective control of performance parameters, but also the production and communication of more complex artistic content (either musical or extra-musical). Therefore, a second category of music expression-related parameters is needed to account for this essential aspect of the creative work of music performers. This category encompasses both music structure elements and concepts (e.g., phrasing, melodic and harmonic tension; Bigand \u0026amp; Parncutt, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) and extra-musical or semantic content (extra-musical ideas, such as a specific narrative, a picture, an emotion, a physical movement metaphor, and so on; H\u0026eacute;roux \u0026amp; Fortier, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Juslin \u0026amp; V\u0026auml;stfj\u0026auml;ll, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). As these music expression-related parameters usually refer to complex musical and extra-musical ideas rather than to specific parameters, we name them abstract parameters in this review for writing and reading simplification purposes. These abstract parameters are usually associated with sound-facilitating gestures in music research literature addressing musicians\u0026rsquo; gestures, which have been studied in relation to structural music elements (e.g., phrasing and music tension; Vines et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) and music expression playing conditions (Davidson, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Thompson \u0026amp; Luck, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Massie-Laberge et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Studies investigating sound-facilitating gestures have used various data collection tools similar to the ones used in the field of biomechanics, particularly 3D motion capture systems, while focusing often on markers\u0026rsquo; linear kinematics rather than on more advanced methods intended to analyze human movement. These studies have shown that changes in music expression conditions (e.g., normal, exaggerated, and deadpan playing conditions) impact both movement of markers placed on performers\u0026rsquo; body and the overall duration of the musical excerpt played (Thompson \u0026amp; Luck, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Massie-Laberge et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePerformance and abstract parameters are closely interrelated: abstract parameters can impact or inform performers\u0026rsquo; choices in relation to performance parameters, and changes in performance parameters might result in changes in abstract parameters. Despite this interrelated nature, the literature addressing how performance and abstract parameters influence musicians\u0026rsquo; gestures have evolved in silos. Sound-producing gestures have been mainly addressed by studies focusing on the biomechanics of music performance, while sound-facilitating gestures have been addressed by empirical music research studies focusing on cognitive, musical, and learning aspects of music performance from an embodied cognition theoretical perspective. As a result, there is currently a lack of dialogue between the studies addressing the impact of performance and abstract parameters related to music expression on pianists\u0026rsquo; kinematics and muscle activity.\u003c/p\u003e \u003cp\u003eThis systematic review aimed to establish a dialogue between experimental research on expert pianists\u0026rsquo; sound-producing and sound-facilitating gestural functions through three research questions. First, we investigated how both performance and abstract parameters related to music expression impact the kinematics and muscle activity of expert pianists. Second, we addressed the following two complementary research questions: \u003cem\u003ei\u003c/em\u003e) what are the ontological and methodological differences between the available studies on music expression and pianists\u0026rsquo; gestures, and \u003cem\u003eii\u003c/em\u003e) how music expression-related parameters affect pianists\u0026rsquo; exposure to risk factors of PRMDs.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe present systematic review was reported in accordance with Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines (Page et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSearch strategy\u003c/h2\u003e \u003cp\u003eA professional university librarian assisted with the creation and execution of the search strategy. Keywords within each concept were combined with the OR Boolean operator, and three concepts were combined with the AND Boolean operator (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The electronic databases OVID (Medline, Embase), EBSCO (SPORTDiscus with Full Text) and CLARIVATE (Web of Science) were systematically searched. The last search was performed on December 14, 2022. Following the search, all identified studies were collated and uploaded into EndNote (X9, Clarivate Analytics, USA) and duplicates were removed. Then, references were uploaded to the Web-based system review software Covidence for the study selection process.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eConcept and keywords used to identify relevant articles.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConcept\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelated keywords\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParticipant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePiano OR pianist\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMusic expression-related parameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eperformance OR expressive OR expression OR \u0026ldquo;musical structure\u0026rdquo; OR \u0026ldquo;structural parameters of pieces\u0026rdquo; OR intention OR communication OR patterns OR loudness OR louder OR tempo OR tempi OR duration OR velocity OR velocities OR \u0026ldquo;sound intensity\u0026rdquo; OR timing OR rhythm OR articulation OR timbre OR \u0026ldquo;musical tension\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKinematics and muscle activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMovement OR motion OR gesture OR kinematic OR biomechanics OR electromyography OR electromyogram OR electromyograph OR muscle OR muscular OR position OR posture\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEligibility criteria\u003c/h3\u003e\n\u003cp\u003ePublications in English in peer-reviewed journals were included. Specifically, the focus centered on experimental studies on piano involving expert or professional adult pianists. The task was required to be a musical excerpt or a series of notes, encompassing either isolated keystrokes (such as repeated notes or octaves) or technical melodic exercises (such as scale or arpeggio tasks). Consistency across participants was a key requirement: all participants were to undertake the same task. Moreover, the designated task had to incorporate at least one change in expression-related parameters: performance parameters (e.g., sound intensity, articulation, tempo), abstract parameters (e.g., use of experimental conditions such as deadpan, immobile, normal, exaggerated), or type of playing context used (e.g., tone sequences, chord sequences, etc.). Lastly, the dependent variable for analysis was required to be based on the measurement of pianist muscle activity and/or kinematics during the piano task.\u003c/p\u003e \u003cp\u003eConversely, studies with only novices or studies comparing novices and experts were excluded. Additionally, studies focusing on the analysis of performance parameters without a formal analysis of gestural features (muscle activity or kinematics) were excluded. Finally, studies involving duo performance were excluded (as it involves additional elements, such as synchronization and communication with the other performer, that are not present in a solo piano performance and may therefore introduce risk of interference).\u003c/p\u003e\n\u003ch3\u003eStudy selection\u003c/h3\u003e\n\u003cp\u003eA first screening was performed using only titles followed by a second screening of abstracts performed by two independent reviewers (authors RM and CT). This process determined whether a study was to be included based on the predetermined eligibility criteria, while minimizing reviewer bias. Subsequently, a final sorting was performed by two authors (RM and CT) using the full texts of the remaining studies. The list of selected articles was discussed between authors until consensus was achieved. All authors\u0026rsquo; conflicts were discussed internally and resolved by a third author (FV).\u003c/p\u003e\n\u003ch3\u003eQuality assessment\u003c/h3\u003e\n\u003cp\u003eThe methodological quality of the studies included in this review was evaluated by two independent reviewers (RM, FV) using a modified version of the Downs and Black checklist (Downs and Black, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Out of 27 items, eleven items were identified as relevant by the authors which allows to evaluate overall reporting bias (items 1, 2, 3, 4, 6, 7, 10), and internal validity bias (items 16, 18, 20, 23) of the included studies. For this review, two items were replaced to ensure relevance for the investigated literature: item 4 (\u0026ldquo;Are the interventions of interest clearly described?\u0026rdquo;) was replaced by \u0026ldquo;Are the experimental conditions clearly described?\u0026rdquo;, and item 23 (\u0026ldquo;Were study subjects randomized to intervention groups?\u0026rdquo;) was replaced by \u0026ldquo;Were experimental conditions randomized for participants?\u0026rdquo;. The items were scored as 1 (\u0026ldquo;yes\u0026rdquo;), 0 (\u0026ldquo;no\u0026rdquo;), or UD (\u0026ldquo;Unable to Determine). The maximum total consists of 11 points per study. Each study was assigned a score of \u0026ldquo;high\u0026rdquo; (\u0026ge;\u0026thinsp;75%), \u0026ldquo;moderate\u0026rdquo; (60\u0026ndash;74%), \u0026ldquo;low\u0026rdquo; (\u0026le;\u0026thinsp;60%) (Desmyttere et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). When the quality scores differed among the reviewers, consensus was finally reached through discussion.\u003c/p\u003e\n\u003ch3\u003eData extraction\u003c/h3\u003e\n\u003cp\u003eThe details of each study were extracted by the author RM and were verified by two authors (CT or FV) in a table containing \u003cem\u003ei\u003c/em\u003e) general information (author names and year of publication, study design); \u003cem\u003eii\u003c/em\u003e) methodological information (participant characteristics, study type, body segment studied, device used, experimental task, independent variables, and dependent variables); and \u003cem\u003eiii\u003c/em\u003e) main findings.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eInter-rater agreement\u003c/h2\u003e \u003cp\u003eCohen\u0026rsquo;s kappa was calculated to analyze inter-rater agreement for the overall study selection process. Kappa values 0.00\u0026ndash;0.20 indicate poor, 0.21\u0026ndash;0.40 fair, 0\u0026ndash;41\u0026ndash;0.60 moderate, 0.61\u0026ndash;0.80 substantial, and greater than 0.81 almost perfect agreement.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSearch results\u003c/h2\u003e \u003cp\u003eThe search yielded a total of 657 results. Following screening, 38 full-text articles were assessed for eligibility of which 23 were excluded. A total of 15 studies (including a total of 162 participants) were eligible for this review (Fig.\u0026nbsp;1). Inter-rater agreement for the overall study selection process yielded a Cohen\u0026rsquo;s kappa of 0.78, suggesting a substantial agreement between the two authors (RM and CT).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eQuality assessment\u003c/h2\u003e \u003cp\u003eThe median quality score of the included studies was 82% (range from 55\u0026ndash;100%) indicating a moderate to high quality (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Ten studies were of high quality (Dalla Bella \u0026amp; Palmer, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Degrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Furuya et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Goebl \u0026amp; Palmer, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Goubault et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Massie-Laberge et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Thio-Pera et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Verdugo et al., 2020; Wong et al., 2024), four studies were of moderate quality (Sforza et al., 2003; Shoda \u0026amp; Adachi, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Thompson \u0026amp; Luck, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Turner et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and one study was of low methodological quality (Castellano et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMethodological quality assessment scores of included studies using the modified version of Downs and Black checklist. 1\u0026thinsp;=\u0026thinsp;Yes; 0\u0026thinsp;=\u0026thinsp;No; UD\u0026thinsp;=\u0026thinsp;Unable to Determine. Quality score: \u0026ldquo;High\u0026rdquo; (\u0026ge;\u0026thinsp;75%), \u0026ldquo;Moderate\u0026rdquo; (60\u0026ndash;74%), \u0026ldquo;Low\u0026rdquo; (\u0026le;\u0026thinsp;60%). Studies have been classified by the performance/abstract parameter manipulated. Q1: clear aim, Q2: clarity of reporting outcomes, Q3: clarity of participants' characteristics, Q4: clarity of experimental conditions, Q6: description of main findings, Q7: estimation and report of random variability, Q10: reporting actual probability values, Q16: clarity of probable data dredging, Q18: appropriate statistical tests, Q20: accuracy of outcome measures, Q23: randomization of experimental conditions.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMusic-expression related parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAuthor \u0026amp; date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c9\" namest=\"c4\"\u003e \u003cp\u003eReporting\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c13\" namest=\"c10\"\u003e \u003cp\u003eInternal validity (bias)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eScore (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQuality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003ePerformance parameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDalla Bella \u0026amp; Palmer, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eUD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDegrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eUD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFuruya et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eUD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFuruya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGoebl \u0026amp; Palmer, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eUD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGoubault et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSforza et al., 2003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eUD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThio-Pera et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eUD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTurner et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eUD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVerdugo et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAbstract parameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCastellano et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eUD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShoda \u0026amp; Adachi, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThompson \u0026amp; Luck, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eUD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eModerate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMassie-Laberge et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerformance and abstract parameters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWong et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c14\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStudies\u0026rsquo; characteristics\u003c/h2\u003e \u003cp\u003eOut of the fifteen studies included, twelve were cross-sectional studies (Dalla Bella \u0026amp; Palmer, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Degrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Furuya et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Goebl \u0026amp; Palmer, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Goubault et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Massie-Laberge et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sforza et al., 2003; Thio-Pera et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Thompson \u0026amp; Luck, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Verdugo et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e; Wong et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and three were cross-sectional case studies (Castellano et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Shoda \u0026amp; Adachi, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Turner et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Ten studies focused on the modification of performance parameters (Dalla Bella \u0026amp; Palmer, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Degrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Furuya et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Goebl \u0026amp; Palmer, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Goubault et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Sforza et al., 2003; Thio-Pera et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Turner et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Verdugo et al., 2020), four studies focused on the modification of abstract parameters (Castellano et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Massie-Laberge et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Shoda \u0026amp; Adachi, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Thompson \u0026amp; Luck, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), and one study addressed both performance and abstract parameters (Wong et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). To enhance the readability and clarity of this systematic review, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e, which summarizes the findings in each study, has been subdivided in three sections: Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e.A reports on studies investigating changes in performance parameters, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e.B reports on studies investigating changes in abstract parameters, and Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e.C reports on the only study investigating changes in both performance and abstract parameters. The studies in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e.A are classified by the performance parameter manipulated, and the studies in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e.B are presented in chronological order.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eA: Summary of studies included in the review that investigated the impact of changes in performance parameters on kinematics and/or muscle activity of pianists (the column \u0026lsquo;Main outcome\u0026rsquo; summarizes one or maximum two main outcomes relevant for the present literature review).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor \u0026amp; date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy Design\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBody segment studied\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMeasurements\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eExperimental task\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIndependent variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDependent variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMain outcome\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSforza et al., 2003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;5 (3 males, 2 females)\u003c/p\u003e \u003cp\u003eProfessional pianists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRight hand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3D motion capture system\u003c/p\u003e \u003cp\u003eDigital piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eThree tempi: 80, 112 and 160\u0026nbsp;bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOverlapping coefficients between trajectories for all fingers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRepeatability of finger movements was lower in concert pianists than in teachers and learners\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDalla Bella \u0026amp; Palmer, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;4 (1 male, 3 females)\u003c/p\u003e \u003cp\u003e16.3 years of piano performing experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRight hand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3D motion capture system\u003c/p\u003e \u003cp\u003eDigital piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTwo melodies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFive tempi: 60, 180, 210, 240, 250\u0026nbsp;bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean movement amplitude (mm) and mean anticipation time\u0026nbsp;(ms) of peak height for fingers\u003c/p\u003e \u003cp\u003eMean finger velocity\u0026nbsp;(m/s) and mean acceleration\u0026nbsp;(m/s\u0026sup2;)\u003c/p\u003e \u003cp\u003eMIDI data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePeak finger heights preceding keystrokes and key velocity increased as tempo increased\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoebl \u0026amp; Palmer, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;12\u003c/p\u003e \u003cp\u003eAt least 10 years of piano instruction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRight fingers, hand, and wrist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3D motion capture system\u003c/p\u003e \u003cp\u003eDigital piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA melody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTen tempi: 7.0, 8.4, 9.6, 10.7, 11.7, 12.3, 13.3, 14.1, 15.0, and 16.0\u0026nbsp;tones per second\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eJoint angle trajectories for all adjacent finger phalanges, the hand, and the wrist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEach finger joint did not change its relative contributions to the fingertip movements across tempi\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTurner et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;3 (2 professionals and 1 intermediate-level with 11 years of piano study)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase Study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTrunk and right hand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3D motion capture system\u003c/p\u003e \u003cp\u003eGrand piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAn excerpt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eThree tempi: 6, 8, and 10\u0026nbsp;notes/s\u0026nbsp;(N/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eStarting position\u003c/p\u003e \u003cp\u003eInitiation intervals\u003c/p\u003e \u003cp\u003eTrunk range of motion\u0026nbsp;(ROM)\u003c/p\u003e \u003cp\u003eRight hand velocity\u0026nbsp;(m/s)\u003c/p\u003e \u003cp\u003eRight limb coordination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAs tempi increased, trunk and right-hand medio-lateral shifts were more synchronized\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFuruya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;18 (5 males, 13 females)\u003c/p\u003e \u003cp\u003eMore than 15 years of classical music\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRight upper limb (Finger, wrist, elbow, and shoulder joints)\u003c/p\u003e \u003cp\u003e6 Right upper-limb muscles (anterior and posterior deltoid (AD and PD), triceps brachii, biceps brachii, flexor digitorum superficialis (FDS), and extensor digitorum communis (EDC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2D motion capture system (sagittal plane)\u003c/p\u003e \u003cp\u003eEMG\u003c/p\u003e \u003cp\u003eUpright piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRepetitive chord keystrokes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFour loudness levels: piano\u0026nbsp;(p), mezzo-piano\u0026nbsp;(mp), mezzo-forte\u0026nbsp;(mf), and forte\u0026nbsp;(f)\u003c/p\u003e \u003cp\u003eFour tempi: 180, 240, 300, and 360\u0026nbsp;bpm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePeak angular velocity\u0026nbsp;(rad/s) of the shoulder, elbow, wrist, and finger\u003c/p\u003e \u003cp\u003eMean muscle activation\u0026nbsp;(%MVC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eInteraction effect of loudness and tempo on peak angular velocity for all joints except for the elbow, and on muscular activity for all muscles\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFuruya et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;7 (3 males, 4 females)\u003c/p\u003e \u003cp\u003eMore than 15 years of classical-piano training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRight upper limb (upper arm, forearm, hand, and finger)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2D motion capture system (sagittal plane)\u003c/p\u003e \u003cp\u003eUpright piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRepetitive isolated keystrokes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTwo loudness levels: piano\u0026nbsp;(p) and forte\u0026nbsp;(f)\u003c/p\u003e \u003cp\u003ePressed and struck touches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean of joint angles\u0026nbsp;(rad), fingertip and key's\u0026nbsp;(mm) vertical position and velocities\u0026nbsp;(rad/s, mm/s)\u003c/p\u003e \u003cp\u003eMean peak angular velocities\u0026nbsp;(rad/s)\u003c/p\u003e \u003cp\u003eNet joint acceleration\u0026nbsp;(rad/s\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eThe pressed and struck touches effectively took advantage of the distal-to-proximal and proximal-to-distal inter-segmental dynamics, respectively\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVerdugo et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;9 (7 males, 2 females)\u003c/p\u003e \u003cp\u003eHolding or currently pursuing a doctoral degree in piano performance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePelvis, thorax, right upper limb and left lower limb\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3D motion capture system\u003c/p\u003e \u003cp\u003eGrand piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRepetitive isolated keystrokes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEight combinations of these three variables:\u003c/p\u003e \u003cp\u003e1)\u0026nbsp;Body implication (use of trunk and upper-limb motion) or use of only upper-limb motion\u003c/p\u003e \u003cp\u003e2)\u0026nbsp;Touch (pressed or struck)\u003c/p\u003e \u003cp\u003e3)\u0026nbsp;Articulation (staccato or tenuto)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eUpper-limb linear velocities\u0026nbsp;(m/s)\u003c/p\u003e \u003cp\u003eJoint angular contribution\u0026nbsp;(m/s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAll upper-limb segments presented forward velocities during the key descent regardless of touch and articulation. Pelvic anterior rotation effectively contributed to creating forward linear velocities at the upper limb\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDegrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;12 (10 males, 2 females)\u003c/p\u003e \u003cp\u003eProfessional pianists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 Right upper-limb muscles (flexor digitorum superficialis, extensor digitorum communis, biceps brachii, triceps brachii, anterior deltoid, middle deltoid, great pectoral, upper trapezius, serratus anterior)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEMG wireless sensor system\u003c/p\u003e \u003cp\u003eGrand piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRepetitive isolated keystrokes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFour possible combinations of: two types of touch (pressed or struck) and articulation (staccato or tenuto)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTime histories of mean muscle activation\u0026nbsp;(%MVC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eCompared to tenuto articulation, staccato articulation induced a higher muscle activity on shoulder muscles\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoubault et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;49 (30 males, 19 females)\u003c/p\u003e \u003cp\u003eAll participants had at least a university (or equivalent) degree or were enrolled in undergraduate or graduate studies in piano performance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eForearm muscles (finger and wrist flexor and extensor muscles)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49 monopolar EMG electrodes\u003c/p\u003e \u003cp\u003eGrand piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDigital and chord excerpts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDigital and chord excerpt\u003c/p\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRate of perceived exertion\u003c/p\u003e \u003cp\u003eEMG median frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eFinger/wrist extensor muscles showed greater signs of fatigue than finger/wrist flexor muscles\u003c/p\u003e \u003cp\u003ePianists showed extremely different levels of endurance.\u003c/p\u003e \u003cp\u003eMuscle fatigue negatively affected key velocity and note-accuracy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThio-Pera et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;8 (6 males, 2 females)\u003c/p\u003e \u003cp\u003eProfessional piano players\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eForearm muscles (hand and wrist muscles)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32 monopolar EMG electrodes\u003c/p\u003e \u003cp\u003eUpright piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOctaves and three excerpts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOctaves were played in four conditions and two tempi:\u003c/p\u003e \u003cp\u003eFour conditions: spezzate, loading the forearm, the wrist, and the fingers segments, each at a time\u003c/p\u003e \u003cp\u003eTwo tempi: self-paced speed and as fast as possible\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eEMG average map\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDepending on playing contexts, professional pianists consistently load specific finger/wrist muscles, whether performing octaves (extensor muscles) or classical excerpts (flexor muscles)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eB: Summary of studies included in the review that investigated the impact of changes in abstract parameters on pianists\u0026rsquo; kinematics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor \u0026amp; date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy Design\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBody segment studied\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMeasurements\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eExperimental task\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIndependent variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDependent variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMain outcome\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCastellano et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1 female\u003c/p\u003e \u003cp\u003eProfessional concert pianist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase Study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverall body movement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVideo cameras\u003c/p\u003e \u003cp\u003eGrand piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAn excerpt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFive different expressive modes: personal, sad, allegro, serene, and over-expressive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eQuantity of motion of the upper body and the velocity of head movements\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eVelocity of head movements was influenced by expressive modes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShoda \u0026amp; Adachi, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;1 male\u003c/p\u003e \u003cp\u003eProfessional pianist (who studied the piano for 20 years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase Study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverall body movement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVideo cameras\u003c/p\u003e \u003cp\u003eGrand piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTwo excerpts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eThree levels of expression: deadpan, artistic, and exaggerated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eMean value of the movement amplitude\u0026nbsp;(rad)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePianist\u0026rsquo;s range of movement in the artistic condition differed from the other two for a fast, energetic piece, whereas it only differed from the deadpan for a slow, romantic piece\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThompson \u0026amp; Luck, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;8 (3 males, 5 females)\u003c/p\u003e \u003cp\u003eBetween 10 and 20 years of piano-playing experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUpper body (hip, torso, neck, head, shoulders, elbows, wrists, middle fingers)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3D motion capture system\u003c/p\u003e \u003cp\u003eDigital piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAn excerpt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFour expressive intentions: normal, deadpan, exaggerated, immobile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDuration of the performance\u0026nbsp;(sec)\u003c/p\u003e \u003cp\u003eCumulative distance travelled by markers (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMarkers at the head and at the shoulder exhibited more movement per measure, compared to the fingers, wrists, and lower back, for the normal and the exaggerated conditions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMassie-Laberge et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;10 (4 males, 6 females)\u003c/p\u003e \u003cp\u003eThe participants were all graduate or post-graduate students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHands, elbows, shoulders, torso, head, and pelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3D motion capture system\u003c/p\u003e \u003cp\u003eDigital piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThree excerpts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFour expressive conditions: normal, deadpan, exaggerated, and immobile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOverall duration of the performances\u003c/p\u003e \u003cp\u003eCumulative distance travelled by markers (mm)\u003c/p\u003e \u003cp\u003eHead movement recurrence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHead movements are important for communicating different expressive playing conditions and structural features (ascending movements, crescendo dynamics, and at the beginning of the melodic theme and its repetition)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eC: Summary of the study included in the review that investigated the impact of changes in both performance and abstract parameters on pianists\u0026rsquo; kinematics.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor \u0026amp; date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy Design\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBody segment studied\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMeasurements\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eExperimental task\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIndependent variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eDependent variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMain outcome\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWong et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;15 (3 males, 12 females)\u003c/p\u003e \u003cp\u003eCompleted Level 9 music training or majored in piano at university at the time or before the data collection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUpper body (head, neck, trunk, sacrum, great trochanter, forearm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3D motion capture system\u003c/p\u003e \u003cp\u003eDigital piano\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA scale and an excerpt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eThree expressive conditions: deadpan (no variation in dynamics or tempo), projected (played as they normally would in a performance), exaggerated (exaggerate all expressive features: tempo, dynamics)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSpine angles for each segment\u0026nbsp;(deg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSpine joint angles showed an average posture closer to neutral 1)\u0026nbsp;in the deadpan playing compared to projected and exaggerated conditions, and 2)\u0026nbsp;in playing an excerpt, compared to playing a scale\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eImpact of performance parameters on pianists\u0026rsquo; kinematics\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003eTechnical Melodic Exercises\u003c/h2\u003e \u003cp\u003eAs tempo increased in technical melodic exercises, one study showed that mean movement vertical amplitude averaged across all fingers increased (from ~\u0026thinsp;17 mm with a tempo of 60 beats per minute (bpm) to ~\u0026thinsp;27 mm with a tempo of 250 bpm) and key velocity increased (from ~\u0026thinsp;43 MIDI units with a tempo of 60 bpm to ~\u0026thinsp;68 MIDI units with a tempo of 250 bpm; Dalla Bella \u0026amp; Palmer, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Another study showed that finger joints did not change their relative contributions to the vertical fingertip movements across tempi; only the wrist vertical movement contributed slightly more to the fingertip motion at fast tempi than at slow tempi (from a wrist vertical efficiency score of ~\u0026thinsp;0/1 with a tempo of 7 tones per second to a wrist vertical efficiency score of ~\u0026thinsp;0.3/1 with a tempo of 15 tones per second; Goebl \u0026amp; Palmer, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eIsolated Keystrokes\u003c/h2\u003e \u003cp\u003eWith an increase of tempo (from 180 bpm to 360 bpm and with a loudness of \u003cem\u003eforte\u003c/em\u003e) during isolated keystrokes, Furuya et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) showed that peak angular velocities increased at the shoulder (from ~\u0026thinsp;0.3 to ~\u0026thinsp;0.37 rad/s) and the wrist (form ~-1.8 to ~-2.1 rad/s), but decreased at the elbow (from ~-2.2 to ~-1.3 rad/s). As loudness increased (from \u003cem\u003epiano\u003c/em\u003e to \u003cem\u003eforte\u003c/em\u003e and with a tempo of 180 bpm), peak angular velocities increased at all joints (shoulder: from ~\u0026thinsp;0.14 to ~\u0026thinsp;0.3 rad/s, elbow: from ~-0.7 to ~-2.2 rad/s, wrist: from ~-1.2 to ~-1.8 rad/s, and finger joints: from ~-1.8 to ~-2.5 rad/s; Furuya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Verdugo et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e) found that shoulder-girdle joints contribution to finger upward velocity was greater during \u003cem\u003estaccato\u003c/em\u003e articulation compared to \u003cem\u003etenuto\u003c/em\u003e articulation (absolute difference\u0026thinsp;=\u0026thinsp;0.207 m/s, percentage difference\u0026thinsp;=\u0026thinsp;206%). These authors also showed that pianists produced systematically forward upper-limb velocities during isolated keystroke attack and key holding/release phases regardless of the choice of articulation and touch.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eRepertoire Excerpts and Mixed Tasks\u003c/h2\u003e \u003cp\u003eWong et al. (\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found that spine joint angles showed an average posture closer to neutral while playing an excerpt (head tilt of 3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u0026deg; in projected playing), compared to playing a scale (head tilt of -4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9\u0026deg;). One study showed that trunk and right-hand movement were more synchronized at faster tempi when playing an excerpt (Turner et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Moreover, when averaging between the three musical sections, the shortest pianist (1.65 m) had the greatest trunk range of motion (276 mm), and the tallest pianist (1.90 m) had the smallest trunk range of motion (101 mm).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eImpact of abstract parameters on pianists\u0026rsquo; kinematics\u003c/h2\u003e \u003cp\u003eThree out of five studies found that playing conditions with a higher level of expressiveness (e.g., deadpan compared to normal, normal compared to exaggerated) resulted in more head and proximal movements compared to deadpan condition (Castellano et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Massie-Laberge et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Thompson \u0026amp; Luck, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). For example, Thompson \u0026amp; Luck (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) found that the distance travelled by the right and the left shoulder was between ~\u0026thinsp;200 to ~\u0026thinsp;300 mm per measure for the exaggerated conditions, and between ~\u0026thinsp;10 to ~\u0026thinsp;50 mm per measure in the deadpan condition. Similarly, Shoda \u0026amp; Adachi (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) found that a pianist increased upper body movements in the artistic and exaggerated conditions compared to the deadpan condition. In addition, one study found that spine joint angles showed an average posture closer to neutral in the deadpan playing (craniovertebral angle of 43.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u0026deg;), compared to the other two conditions (craniovertebral angle of 38.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u0026deg; and 37.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u0026deg; for the projected and exaggerated conditions, respectively; Wong et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eImpact of performance parameters on pianists\u0026rsquo; muscle activity\u003c/h2\u003e \u003cp\u003eStudies investigating muscle activity focused on isolated keystrokes and musical excerpts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eIsolated Keystrokes\u003c/h2\u003e \u003cp\u003eBoth the activation level of six muscles (anterior and posterior deltoids, biceps brachii, triceps brachii, flexor digitorum superficialis, and extensor digitorum communis) and the co-activation index between the anterior-posterior deltoid, biceps-triceps brachii, and flexor digitorum superficialis-extensor digitorum communis muscle pairs increased at a tempo of 5 keystrokes per second or higher (Furuya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). As loudness increased (from \u003cem\u003ep\u003c/em\u003e to \u003cem\u003emp\u003c/em\u003e, \u003cem\u003emp\u003c/em\u003e to \u003cem\u003emf\u003c/em\u003e, and \u003cem\u003emf\u003c/em\u003e to \u003cem\u003ef\u003c/em\u003e), the activation level of the above-mentioned muscles and their co-activation index increased (Furuya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The activation level particularly increased for distal muscles (the flexor digitorum superficialis, and the extensor digitorum communis increased their muscle activity from ~\u0026thinsp;4\u0026ndash;5% maximum voluntary contraction (MVC) at slow tempi, to ~\u0026thinsp;10% MVC at faster tempi). During and after key descent and release, \u003cem\u003estaccato\u003c/em\u003e articulation showed a higher activity in the shoulder muscles, compared to tenuto articulation (upper trapezius\u0026thinsp;+\u0026thinsp;2.1% MVC, anterior deltoid\u0026thinsp;+\u0026thinsp;2.5% MVC, great pectoralis\u0026thinsp;+\u0026thinsp;3.8% MVC; Degrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). One study showed that professional pianists activated more finger/wrist extensor muscles than finger/wrist flexor muscles when performing octaves (Thio-Pera et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eMusical Excerpts\u003c/h2\u003e \u003cp\u003eThio-Pera et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) showed that professional pianists activated more finger/wrist flexor muscles than finger/wrist extensor muscles when performing repertoire excerpts compared to octaves. Constant repetition of a digital exercise and a chord musical excerpt, both performed loud and fast, showed higher levels of muscle fatigue at finger/wrist extensor muscles (the EMG median frequency decreased between 10 and 20 Hz at task termination) compared to the respective flexors (the EMG median frequency decreased between 2 and 10 Hz), and pianists showed different levels of endurance in their time-to-task termination (from around 2 min to 12 min, which was the maximum time allowed for the task; Goubault et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eOntological and methodological choices\u003c/h2\u003e \u003cp\u003eOntological choices (focus of studies, gestural variable investigated) and methodological choices (kinematic and EMG data collection tools, experimental tasks, musical instrument used) are reported in Fig.\u0026nbsp;2. Regarding kinematic analysis, the gestural variables investigated were different between studies focusing on the modification of performance parameters and studies focusing on abstract parameters. Studies focusing on the modification of performance parameters assessed either \u003cem\u003ei\u003c/em\u003e) finger and/or wrist linear velocities (Dalla Bella \u0026amp; Palmer, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Turner et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), joint angles (Goebl \u0026amp; Palmer, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and movement repeatability (Sforza et al., 2003) ; and \u003cem\u003eii\u003c/em\u003e) right upper limb (Furuya et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) or upper body (Verdugo et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e) linear and joint kinematics (e.g., joint angular velocities, segmental linear velocities, etc.). Studies focusing on abstract parameters measured either \u003cem\u003ei\u003c/em\u003e) the quantity of motion, (i.e., an approximation of the amount of detected movement, based on Silhouette Motion Images, which represent all variations of a simplified white-body silhouette, obtained using background subtraction; Castellano et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and the cumulative distance travelled by markers (Massie-Laberge et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Thompson \u0026amp; Luck, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e); or \u003cem\u003eii\u003c/em\u003e) postural angles of the spine (Shoda \u0026amp; Adachi, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Wong et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Regarding EMG analysis, two studies calculated mean muscle activation over the entire trial (Furuya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Thio-Pera et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), one study calculated time series muscle activation (Degrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and one study calculated the EMG median frequency to assess the myoelectric manifestation of muscle fatigue (Goubault et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eRisk factors of playing-related musculoskeletal disorders\u003c/h2\u003e \u003cp\u003eA complementary objective was to address how music expression affects pianists\u0026rsquo; exposure to risk factors of PRMDs. Risk factors of PRMDs associated with music expression could only be extracted from the studies focusing on performance parameters. The type of task, playing factor, and biomechanical impact addressed by these studies are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Four playing factors have been identified as potential risk factors of PRMDs: playing loud, playing fast, \u003cem\u003estaccato\u003c/em\u003e articulation, and large handspan chords (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eType of tasks, playing factors, and biomechanical impacts of included studies.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor \u0026amp; date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of task\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlaying factor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBiomechanical impact\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDalla Bella \u0026amp; Palmer, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMelodic exercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlaying fast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncrease in fingertip height\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDegrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsolated keystrokes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eStaccato\u003c/em\u003e articulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncrease in shoulder muscle activation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFuruya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIsolated keystrokes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlaying loud and fast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncrease in muscle activation of six upper limb muscles (anterior and posterior deltoids, biceps brachii, triceps brachii, flexor digitorum superficialis, and extensor digitorum communis)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGoubault et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRepetitive melodic and chord tasks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlaying loud and fast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncrease in finger/wrist extrinsic extensor muscle fatigue\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThio-Pera et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsecutive octaves\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLarge handspan chords\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncrease in finger/wrist extensor muscle activity\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis systematic review investigated how both performance and abstract parameters of music expression impact pianists\u0026rsquo; gestures. It also addressed ontological and methodological differences of the included studies and the impact of music expression-related parameters on exposure to risk factors of PRMDs. Fifteen studies were included. Ten studies focused on the modification of performance parameters (i.e., sound intensity, tempo, articulation), four studies focused on the modification of abstract parameters (structural and/or semantic), and one study focused on both. Performance and abstract parameters impacted pianists\u0026rsquo; kinematics and muscle activity, the specific effects being dependent on the type of task (i.e., isolated tones, digital task, chord task) and the gestural variable investigated by studies. Important differences in ontological (performance or abstract parameters studied, gestural variable investigated) and methodological choices (experimental task and instrument used, data acquisition and processing procedures) prevent the establishment of a thorough dialogue between studies focusing on performance and abstract parameters. Risk factors of PRMDs associated with music expression parameters included playing loud, playing fast, \u003cem\u003estaccato\u003c/em\u003e articulation, and playing large handspan chords.\u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eImpact of music expression on pianists\u0026rsquo; gestures\u003c/h2\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eLoudness and articulation\u003c/h2\u003e \u003cp\u003eIn isolated keystrokes, loudness and articulation had clear and consistent effects across studies. An increase in loudness led to greater angular velocities and muscle activity at both distal and proximal joints/segments of the right upper limb (Furuya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). These results are consistent with piano sound-production mechanics, as loudness is closely related to the key attack velocity (e.g., Dannenberg, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). To increase the targeted key velocity of louder tones, pianists increased velocity and muscle activity at upper-limb joints (shoulder, elbow, wrist). Articulation had a similar effect, but in relation to the release motion. \u003cem\u003eStaccato\u003c/em\u003e articulation (in opposition to \u003cem\u003etenuto\u003c/em\u003e articulation) increased upper-limb upward/forward velocities (Verdugo et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and shoulder muscle activity (Degrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) during and after the key descent in the context of isolated keystrokes, as the shoulder-girdle joints were the primary mover of the rapid lifting motion of the arm and hand after the attack (Verdugo et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In brief, the production of faster key attack (louder tones) and key release (\u003cem\u003estaccato\u003c/em\u003e tones) movements demands an increased velocity and muscle activity at the joints responsible for those faster endpoint movements. These studies have been conducted on simple performance tasks (repetitive isolated keystrokes). However, in more complex musical contexts, it seems possible to hypothesize that the same relation may prevail (i.e., increase of joint velocity and muscle activity allowing faster key attack and release movements).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eTempo\u003c/h2\u003e \u003cp\u003eIn the case of technical melodic exercises, an increase in tempo led to an increase in the height of the fingers before the keystroke (Dalla Bella \u0026amp; Palmer, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The most important finger joint to produce the fingertip vertical movement during this type of melodic exercises was the metacarpophalangeal joint, and its contribution remained stable across different tempi (Goebl \u0026amp; Palmer, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These results point to two ideas. First, faster tempi impose spatiotemporal constraints that require an increased distance between the fingertip and the key before the attack to produce the targeted key attack velocity. Second, this increased height of the fingertip might increase the extension motion of the metacarpophalangeal joint. Furuya et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) showed that during fast alternate keystrokes (i.e., tremolo), expert pianists used hand pronation/supination (a degree of freedom at the elbow) to reduce metacarpophalangeal muscle load. As pianists can use pronation/supination not only during alternate keystrokes but also during a wide range of melodic passages (scales, arpeggios, etc.), the increased finger height at faster tempi reported by Dalla Bella \u0026amp; Palmer (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) could be achieved by multi-joint hand/forearm movements rather than by isolated metacarpophalangeal joint movements. Dalla Bella \u0026amp; Palmer (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) did not address interactions of loudness and tempo in their study. However, as louder sounds entail faster joint and key velocities, the required finger height needed to play at a certain tempo might also be affected by the targeted sound intensity. This must nevertheless be confirmed by future research.\u003c/p\u003e \u003cp\u003eDuring repetitive isolated keystrokes, varying the tempo produced distinct effects on peak angular velocities at different joints. Despite the interactions between loudness and tempo reported in Furuya et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), these authors observed that an increase in tempo resulted in faster peak flexion/extension velocities at the shoulder and wrist and slower peak velocities at the elbow. Similarly, two recent studies showed a reduction of elbow flexion/extension range of motion while playing repetitive chords at faster tempi (Turner et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Wang et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). If elbow extension was the main contributor of the fingertip downward attack velocity during slow isolated keystrokes (Verdugo et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e), the results of the above-mentioned studies show that the leading role of the elbow to produce the attack downward velocity of the fingertip decreases while tempo increases. However, this tempo-dependent change of inter-joint coordination did not imply a reduction of elbow muscle activity, as faster tempi produced greater mean muscle activity at proximal and distal joints of the upper limb and higher co-contraction levels of elbow and finger muscles (Furuya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eType of task\u003c/h2\u003e \u003cp\u003eThio-Pera et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) found different task-dependent finger/wrist muscle loads regardless of tempo, where consecutive octaves induced greater activations at extrinsic extensors while other types of excerpts (melodic \u0026lsquo;finger\u0026rsquo; passage, slow-loud chord passage) induced greater activations at extrinsic flexors. To play consecutive octaves, pianists constantly hold the hand in a fixed position characterized by finger extension/abduction (which is coherent with the increased activity of extrinsic extensors reported by the authors). This is not the case in the other excerpts used in Thio-Pera et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), as distal joint posture and movements can be adapted at each keystroke or group of keystrokes. Chong et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) also found that muscle activation in hand extrinsic muscles was dependent on the configuration of the notes imposed in the score. However, Goubault et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found higher levels of fatigue at finger/wrist extrinsic extensor muscles (compared to flexors) regardless of the type of task. Extensor muscles showed higher signs of fatigue during both a chord passage (involving octaves) and a melodic \u0026lsquo;finger\u0026rsquo; passage played repetitively in cycles. These results suggest that even though muscle load is dependent on note configuration (i.e., task dependent muscle load), muscle fatigue might greatly affect specific muscles due to their intrinsic characteristics or the duration of the repetitive activations.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAbstract parameters and gestural functions\u003c/b\u003e \u003c/p\u003e \u003cp\u003eRegarding abstract parameters, Thompson \u0026amp; Luck (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and Massie-Laberge et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found that playing conditions with a higher level of expressiveness (e.g., deadpan compared to normal, normal compared to exaggerated) resulted in more movement at markers placed on the head and proximal segments. These findings underline the role of performers\u0026rsquo; whole-body movements as a tool to encode or embody the expressive content of music while playing (Krumhansl, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Leman \u0026amp; Maes, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). These gestures have been associated with sound-facilitating gestures (or ancillary gestures) by the cited studies and the related literature (Massie-Laberge et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Thompson \u0026amp; Luck, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Wanderley et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). However, delimitation of what body movements are labelled as sound-facilitating and as sound-producing is not clearly addressed. Typically, in this literature, sound-facilitating gestures involve the trunk and the head, while sound-producing gestures involve distal segments close to the performer-instrument interface (forearm, hand, fingers; Jensenius et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Thus, these two types of gestures are usually understood as distinct gestures and have been studied separately in the literature. However, Verdugo et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e) showed that pianists\u0026rsquo; pelvis and thorax movements can play a role in the control of performance parameters related to articulation and loudness. Moreover, other recent studies have also highlighted the role of trunk motion in pianists\u0026rsquo; sound-production strategies (Turner et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Verdugo et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In the case of piano performance, it therefore seems clear that sound-producing and sound-facilitating gestures are not distinct gestures but are rather gestural functions embedded in the same gestural space incorporating the entire kinematic chain (pelvis, thorax, upper limbs, and potentially lower limbs). To enhance dialogue and coherence between the literature addressing the impact of performance and abstract parameters on pianists\u0026rsquo; gestures, we recommend a more systematic use of the concepts of sound-producing and sound-facilitating \u003cem\u003egestural functions\u003c/em\u003e, rather than sound-producing and sound-facilitating \u003cem\u003egestures\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eOntological and methodological differences of the targeted literature\u003c/h2\u003e \u003cp\u003eOne of the main ontological differences of the studies in this review relates to the type of music expression-related parameters investigated. The ten studies addressing performance parameters focused on \u0026lsquo;score-imposed\u0026rsquo; variations of performance parameters. For example, playing the same task at the piano with different imposed tempi (e.g., Sforza et al., 2003), different articulation (e.g., Degrave et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and different loudness levels (e.g., Furuya et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In addition, these studies, generally from the field of biomechanics and motor control, did not consider abstract parameters (music structure parameters and extra-musical or semantic ideas) from research questions. On the contrary, studies from the music research domain addressing abstract parameters investigated the effect of music expression on pianists\u0026rsquo; gestures in relation to the performers\u0026rsquo; interpretation of the score. By using notions such as expressive intentions and experimental conditions based on different levels of expression (deadpan, normal, exaggerated), these studies addressed music expression from the performers\u0026rsquo; point of view. This different focus on expression (score-imposed features versus performers\u0026rsquo; interpretation features) is a key difference that hampers the establishment of a connection between research on musicians\u0026rsquo; gestures from biomechanics and motor control, on one hand, and from music research and empirical musicology, on the other hand. Biomechanical studies addressing the impact of pianists\u0026rsquo; personal management of abstract parameters would be necessary to strengthen the link between literature from biomechanics and music research, and enable a deeper understanding of the impact of music expression (linked to the creative work not only of the composer but also of the performer) on pianists\u0026rsquo; gestures.\u003c/p\u003e \u003cp\u003eA key methodological difference in studies focusing on pianists\u0026rsquo; kinematics relates to the choice of the kinematic variable investigated. It is noteworthy that most studies (eight out of twelve focusing on pianist\u0026rsquo;s kinematics) used 3D motion capture systems (Fig.\u0026nbsp;2). Despite one exception (Wong et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), studies on pianists\u0026rsquo; sound-facilitating gestures analyzed segmental kinematics based on data of markers placed on the body (e.g., quantity of motion, distance travelled by markers), with little or no attention to joint kinematics or more thorough methods for the computation of segmental kinematics (using for example segment endpoint or center of mass). Therefore, studies in music research do not usually take advantage of methods from biomechanics to analyze and address the interdependent nature of movements of multi-body systems such as the human body. An interdisciplinary approach mixing methods from empirical musicology and biomechanics would, first, facilitate a better understanding of the interrelated nature of sound-producing and sound-facilitating functions in the context of multi-joint movements of pianists. Second, as abstract parameters might not only affect pianists\u0026rsquo; kinematics but also muscle activity (Verdugo et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), this interdisciplinary approach would allow to assess the impact of pianists\u0026rsquo; expressive intentions on their muscle load, with implications for both embodied cognition and injury prevention research. As an example, in a recent case study on two participants, Mailly et al., 2024 showed that pianists can embody their expressive intentions in different musical contexts through upper-body muscle activity, including proximal (upper trapezius, external oblique,) and distal muscles, such as flexor digitorum superficialis and extensor digitorum communis.\u003c/p\u003e \u003cp\u003eAnother important methodological difference was associated with the instrument used. Six studies used a grand piano, six studies used a digital piano, and three studies used an upright piano (Fig.\u0026nbsp;2). Acquiring pianists\u0026rsquo; movements using optoelectronic cameras and passive markers remains a challenge due to marker occlusions caused by the piano itself. Despite this obstacle, several studies have been conducted with grand piano using these motion capture systems (Turner et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Verdugo et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The grand piano is the actual instrument where pianists usually perform and practice and its specific key action mechanism influences pianists\u0026rsquo; touch and sound control (Traube et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Therefore, the use of digital instruments to facilitate motion capture procedures may change how pianists manipulate both performance and abstract music expression-related parameters, and consequently, influence research results. This methodological limitation was highlighted in a previous literature review on piano touch (MacRitchie, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, it remains relevant for the current state of the literature.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eRisk factors of PRMDs and considerations for injury prevention\u003c/h2\u003e \u003cp\u003eThe following four playing factors were associated with increased muscle load or muscle fatigue: playing loud, playing fast, \u003cem\u003estaccato\u003c/em\u003e articulation, and playing large handspan chords. The included studies in this review did not address the relationship between the reported increase of muscle activation or fatigue and PRMDs history in the participants recruited. Nevertheless, increases in muscle load and muscle fatigue are typically considered prominent risk factors of musculoskeletal disorders in music (Ling et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), sports, and daily life activities (C\u0026ocirc;t\u0026eacute;, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). In addition, questionnaire-based studies have shown that large handspan chords (such as octaves; Allsop, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Sakai, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Shields \u0026amp; Dockrell, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), and playing chords loudly (Furuya et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) were associated to the development of PRMDs. In this direction, future studies should investigate gestural strategies that can reduce exposure to the four above-listed risk factors. Moreover, considering that these playing factors are extremely common in the piano repertoire, quantification of practice load based on these playing factors might also help reduce occurrence of pianists\u0026rsquo; PRMDs.\u003c/p\u003e \u003cp\u003eRecent studies in sport science literature focusing on injury prevention (e.g., running, tennis) have centered on the concept of \u0026lsquo;training load\u0026rsquo; (Coutts et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Drew \u0026amp; Finch, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Gabbett, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Training load is quantified by multiplying the duration of each training session by its intensity, usually assessed using the perception of effort on a scale of 1 to 10 (Foster et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Subsequently, the evolution of the training load is assessed on a weekly basis. Literature has shown that when training load increases by more than 15% above the previous week training load, prevalence of injury increases by 21\u0026ndash;49% (Gabbett, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Therefore, it has been concluded that to minimize the risk of injuries in athletes, it is advisable to maintain training load weekly increases below 10%. While the concept of playing load has recently been studied in relation to music performance (McCrary et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), monitoring playing load based on the playing factors identified in this review as a prevention strategy of PRMDs has yet to be studied. Therefore, future studies could develop playing load models to both quantify playing load and its fluctuation and predict occurrence of PRMDs in pianists, especially during the preparation process of upcoming performances or music competitions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eLimitations of this systematic review include search strategy and methodological differences between studies. First, limitations in database coverage may have resulted in some relevant studies being overlooked. However, the search strategy was performed in 4 databases, which improved coverage, and decreased the risk of making inappropriate conclusions (Ewald et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Second, the included studies differed in their design (cross-sectional studies or case studies). The studies also varied in their focus, addressing different parameters (performance or abstract parameters, or both), type of tasks (i.e., isolated tones, digital task, chord task, musical excerpts) and gestural variables investigated (linear segmental kinematics, joint angles, muscle activity), which limited the comparison between studies. However, most of the included studies showed a moderate to high methodological quality assessment score, suggesting that the overall quality of the results was not compromised.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis systematic review investigated how both performance parameters (timing, sound intensity, articulation) and abstract parameters (related to music structure and extra-musical or semantic content) of music expression impact pianists\u0026rsquo; gestures. We also addressed ontological and methodological differences, and how music expression-related parameters affected pianists\u0026rsquo; exposure to risk factors of PRMDs. Performance and abstract parameters impacted pianists\u0026rsquo; kinematics and muscle activity, the specific effects being dependent on the type of task and the gestural variable investigated by studies. Important differences in ontological (performance or abstract parameters studied, gestural variable investigated) and methodological choices (experimental task and instrument used, data acquisition and processing procedures) prevent the establishment of a thorough dialogue between studies focusing on performance and abstract parameters. Four playing factors (playing loud, playing fast, \u003cem\u003estaccato\u003c/em\u003e articulation, and large handspan chords) were identified as potential risk factors of PRMDs. To enhance the dialogue and coherence between the literature addressing the impact of performance and abstract parameters on pianists\u0026rsquo; gestures, two avenues can be proposed. First, the use of a more precise terminology to designate the pianists' gestures. As sound-producing and sound-facilitating gestures are embedded in the same gestural space, a more systematic use of the concepts of sound-producing and sound-facilitating \u003cem\u003egestural functions\u003c/em\u003e is recommended, rather than sound-producing and sound-facilitating \u003cem\u003egestures\u003c/em\u003e. Second, a multidisciplinary approach may be needed to bridge the gap between studies from empirical music research and biomechanics. In this direction, future studies in empirical music research could make use of joint kinematics and muscle activity analysis used in biomechanics. Similarly, future studies in biomechanics and motor control could focus on the abstract parameters of musical expression. This could help develop a more comprehensive knowledge on the impact of music expression on pianists\u0026rsquo; gestures for both performance and injury prevention purposes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Social Science and Humanities Research Council of Canada (Insight Development Grant 430-2021-00384).\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eWe would like to thank Denis Arvisais (librarian at University of Montreal) for his help in the creation and execution of the search strategy.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors have no conflict of interest to report.\u003c/p\u003e\n\u003cp\u003eEthical approval\u003c/p\u003e\n\u003cp\u003eThis research did not require ethics committee or IRB approval. This research did not involve the use of personal data, fieldwork, or experiments involving human or animal participants, or work with children, vulnerable individuals, or clinical populations.\u003c/p\u003e\n\u003cp\u003eData availability statement\u003c/p\u003e\n\u003cp\u003eData sharing not applicable to this article as no datasets were generated or analyzed during the current study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAllsop, L. (2007). Investigating the Prevalence of Playing-Related Musculoskeletal Disorders in Relation to Piano Players\u0026rsquo; Playing-Techniques and Practising Strategies. 147.\u003c/li\u003e\n \u003cli\u003eBernays, M., \u0026amp; Traube, C. (2014). Investigating pianists\u0026rsquo; individuality in the performance of five timbral nuances through patterns of articulation, touch, dynamics, and pedaling. 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Frontiers in Psychology, 13, 838554. https://doi.org/10.3389/fpsyg.2022.838554\u003c/li\u003e\n \u003cli\u003eTurner, C., Visentin, P., Shan, G., \u0026amp; Turner, vin. (2021). Wrist Internal Loading and Tempo-Dependent, Effort-Reducing Motor Behaviour Strategies for Two Elite Pianists. Medical Problems of Performing Artists, 36(3), 141\u0026ndash;149. https://doi.org/10.21091/mppa.2021.3017\u003c/li\u003e\n \u003cli\u003eVerdugo, F., Begon, M., Gibet, S., \u0026amp; Wanderley, M. M. (2022). Proximal-to-Distal Sequences of Attack and Release Movements of Expert Pianists during Pressed-Staccato Keystrokes. Journal of Motor Behavior, 54(3), 316\u0026ndash;326. https://doi.org/10.1080/00222895.2021.1962237\u003c/li\u003e\n \u003cli\u003eVerdugo, F., Ceglia, A., Frisson, C., Burton, A., Begon, M., Gibet, S., \u0026amp; Wanderley, M. M. (2022). Feeling the Effort of Classical Musicians\u0026mdash;A Pipeline from Electromyography to Smartphone Vibration for Live Music Performance. 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Postural Variability in Piano Performance. Music \u0026amp; Science, 5, 205920432211378. https://doi.org/10.1177/20592043221137887\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"piano performance, expressive intentions, biomechanics, EMG, PRMDs","lastPublishedDoi":"10.21203/rs.3.rs-5204526/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5204526/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBodily gestures are essential in piano performance. They allow sound production and, at the same time, facilitate the communication of the expressive content of music. From pianists\u0026rsquo; perspective, music expression-related parameters include not only single performance parameters (timing, sound intensity, articulation, etc.), but also more complex parameters (named hereafter abstract parameters), such as music structure features (e.g., phrasing) and extra-musical ideas (e.g., emotions, narratives, etc.). This systematic review aimed to investigate the impact of both performance and abstract parameters related to music expression on kinematics and muscle activity of expert pianists. As complementary objectives, we documented ontological and methodological differences between the studies included, and we addressed how music expression-related parameters affect pianists\u0026rsquo; exposure to risk factors of injuries. The search strategy consisted of using concepts and keywords in Medline, Embase, SPORTDiscus, and Web of Science databases, and we followed the PRISMA guidelines. Fifteen studies were included. Ten studies focused on performance parameters, four studies focused on abstract parameters, and one study addressed both performance and abstract parameters. Performance and abstract music expression-related parameters impacted pianists\u0026rsquo; kinematics and muscle activity in a variety of ways. The specific effects were dependent on the type of task and the gestural variable investigated by studies. Important differences in ontological (performance or abstract parameters studied, gestural variable investigated) and methodological choices (experimental task and instrument used, data acquisition and processing procedures) prevent the establishment of a thorough dialogue between music research studies and biomechanics and motor control studies. A set of performance parameters (playing loud, playing fast, staccato articulation, large handspan chords) were identified as potential risk factors of injuries. Further interdisciplinary research mixing methods from empirical music research and biomechanics would help enhance knowledge on the impact of music expression on pianists\u0026rsquo; gestures for both performance and injury prevention purposes.\u003c/p\u003e","manuscriptTitle":"Impact of Music Expression-Related Parameters on Pianists’ Kinematics and Muscle Activity: A Systematic Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-08 10:12:09","doi":"10.21203/rs.3.rs-5204526/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b4d46545-dd1d-4e91-a9af-a3e3268dd9b3","owner":[],"postedDate":"October 8th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":38551726,"name":"Music"},{"id":38551727,"name":"Sports Medicine and Kinesiology"}],"tags":[],"updatedAt":"2025-03-03T17:55:38+00:00","versionOfRecord":{"articleIdentity":"rs-5204526","link":"https://doi.org/10.1177/20592043251317019","journal":{"identity":"music-and-science","isVorOnly":true,"title":"Music \u0026 Science"},"publishedOn":"2025-02-27 00:00:00","publishedOnDateReadable":"February 27th, 2025"},"versionCreatedAt":"2024-10-08 10:12:09","video":"","vorDoi":"10.1177/20592043251317019","vorDoiUrl":"https://doi.org/10.1177/20592043251317019","workflowStages":[]},"version":"v1","identity":"rs-5204526","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5204526","identity":"rs-5204526","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}