The Size and Behavior of Virtual Objects have influence on Functional Exercise and Motivation of Persons with Multiple Sclerosis: a randomized study

The Size and Behavior of Virtual Objects have influence on Functional Exercise and Motivation of Persons with Multiple Sclerosis: a randomized study | 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 Article The Size and Behavior of Virtual Objects have influence on Functional Exercise and Motivation of Persons with Multiple Sclerosis: a randomized study Imre Cikajlo, Alma Hukić, Anja Udovčić Pertot This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1707133/v2 This work is licensed under a CC BY 4.0 License Status: Under Review Version 2 posted 10 You are reading this latest preprint version Show more versions Abstract Background : The consequences of multiple sclerosis are problems related to movement of extremities, coordination and vision. Heretofore frequent treatment with additional medications can change the course of the disease. Motor relearning of small range movements are important to support daily living activities. We have designed a virtual environment for pick and place task. The user hand and finger movements were tracked with a small infrared camera. The primary objective of the study was to examine the influence of size and behavior of virtual cubes on motor control, motivation and functional performance. The secondary objective was to examine the changes of heart rate and intensity of the task due to the different size and behavior of the virtual objects. Methods : In the randomized study 84/107 eligible inpatients with multiple sclerosis participated. They were randomized into 4 groups by computer random function; group 1 - small and bouncing, group 2 - small and non-bouncing, group 3 - big and bouncing and group 4 - big and non-bouncing virtual cubes. Each participant took 50 sessions, each up to 2 min in approximately 14 days. Before commencement of the study the participants took visual-spatial and cognitive tests. The participants’ subjective experiences was assessed daily with Intrinsic Motivation Inventory. Box and Blocks Test was carried out before and after the study. Results : In the study the group 4 was the most successful (inserted cubes > 9) and the fastest (63.4 SD 25.8 s). The group 1 was the slowest (88.9 SD 28.2 s), but with high interest/enjoyment rate and pressure/tension at high heart rate. There were substantial differences in intrinsic motivation between the 1st and the last session within the groups (Cohen's U3 0.8). Kinematic analysis showed differences between the groups (average manipulation time p = 0.008, inserted cubes p = 0.004). Conclusions : The size and behavior of virtual objects may be crucial for the motivation of participants with equal visual-spatial and cognitive capabilities while maintaining effort and keep trying to improve their performance. Furthermore, the clinical outcomes can confirm the effectiveness of the approach. Trial registration : The small scale randomized pilot trial has been registered at ClinicalTrials.gov Identifier: NCT04266444, 12/02/2020, https://clinicaltrials.gov/ct2/show/NCT04266444 multiple sclerosis rehabilitation virtual reality exergaming perception upper extremities intrinsic motivation inventory Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1 Background Multiple sclerosis (MS) is a demyelinating disease that affects brain and spinal cord (central nervous system). The MS typically strikes in young adulthood, it is chronic and progressive, and it has a variable and unpredictable course [ 1 ]⁠. The disease is considered an autoimmune disease, attacking the cover of the nerve fibers (myelin) and causing malfunctioning of connections between the brain and the spinal cord. Consequently the “message” in the nerve is obstructed, often blocked. This results in a partial or complete loss of functionalities of daily living; vision problems, speech, aphasia, balance, coordination, fatigue, concentration, bowel & bladder function, functional movement disorders, etc. The disease may lead to a permanent disability. Despite the cause of the MS is not entirely known and no cure has been formally introduced, a management of the symptoms is essential in optimizing participation and quality of life in people with MS. Medications are available to address most of the symptoms [ 2 ]⁠ and can change the course of the disease to the certain level. Care for people with MS should be interdisciplinary. The rehabilitation team consists of a specialist in physical and rehabilitation medicine, a nurse, a physiotherapist, an occupational therapist, a speech and language therapist, a psychologist and a social worker. The team may invite also a dietitian and a prosthetic/orthotics engineer if necessary. Together with the patient the team members define short- and long-term rehabilitation goals, rehabilitation plan and interventions, and monitor and adjust the goals and programmes according to the patient's needs and the stage of the disease [ 3 ]⁠. The effects of the rehabilitation programmes are most commonly estimated by patients' progress on the Expanded Disability Status Scale (EDSS), [ 4 ]⁠, a method of quantifying disability in people with multiple sclerosis and monitoring changes in the level of disability over time, filled by the physician, neurologist or specialist in physical and rehabilitation medicine. Among numerous consequences of MS the upper limb dysfunction is very common and often caused by a tremor, sensory deficits, weakness or loss of dexterity [ 5 ]⁠, [ 6 ]⁠. Loss of motor skills affects activities of daily living (ADL), quality of life and employment status [ 7 ]⁠, [ 8 ]⁠. The clinicians and researchers have been actively developing neuromotor treatments that would effectively restore upper limb functions, raise quality of life and improve prognosis in patients with MS. The neuromotor rehabilitation of patients with MS requires several types of exercises. Virtual reality (VR) and exergaming have been suggested as potential tools [ 9 ]⁠. Several studies successfully applied non-immersive equipment, rarely reported on advantages of fully immersive equipment [ 10 ]⁠ and no evidence has been provided that VR approach would be superior to conventional approaches. However, there are some evidences that VR and exergaming are effective in improving motor function in upper extremities [ 11 ]⁠ and may play an important role in daily living activities. Particularly grasping and fine finger movements may present important tasks for persons with MS. Using virtual objects in exergaming has in contrast to the real world task an ability to modify the target of the desired task, change the object characteristics according to the required level or patients’ visual, motor or cognitive capabilities also in real-time. The objectives of the randomized pilot study were to examine the effects of different sizes and bouncing properties of virtual objects on exergame performance, motivation and clinical outcomes at assumption that participants have had similar visual and cognitive capabilities. 2 Materials And Methods 2.1 Study design A randomized pilot study with patients with MS was designed. Participants were included in the study according to the inclusion and exclusion criteria. Baseline clinical assessment was carried out on the day when the participant was randomized into one of the four specific group. All groups participated in the post-treatment clinical assessment. Primary outcome measures were clinical tests with questionnaire results as a supplement. Exergaming and kinematic results were considered as secondary outcome measures. 2.2 Rehabilitation system The rehabilitation – exergaming system is based on 3D kinematics assessed by the infrared camera system Leap Motion Controller (LMC, Ultraleap Inc. Mountain View, CA, USA) with Orion SDK. The LMC is a small 80 x 30 mm optical tracking device with 140 x 120 Deg field of view and tracking range between 10 and 60 cm. It detects hand and finger movements with adequate accuracy [ 12 ]⁠ and transfers data to the powerful computer with GPU via USB with 100Hz. The robust and reliable skeletal model has been further upgraded in Unity3D (Unity Technologies, CA, USA) and used to track the kinematics of the hand and fingers. Building a virtual model of the hand and combining its kinematics with a scenery in a virtual environment resulted in a handy exergame [ 10 ]⁠. The scenery comprises 10 cubes of various colors, but same size and an open treasure chest in the green virtual field (Fig. 1 ). The goal of the exergame was to pick and place all the cubes by virtual hand into the open chest within two minutes. Specifically for the study we implemented 2 variable parameters: the size and the material of the cubes. The material defined the bouncing characteristics of the cube, while the size of the cube matters when grabbing the object. The user was able to choose from 4 different options combining the size and the (non) bouncing material of the cubes. Figure 1 . about here 2.3 Participants In the randomized pilot study from February 2020 to September 2021 we recruited 107 patients from the local hospital with diagnosed multiple sclerosis (37 male, 70 female, age 51.1 ± 11.5 years) eligible for the study according to the inclusion criteria. The participant were briefly screened for Mini Mental State Examination (MMSE) to assess the severity of cognitive impairment with a maximum score of 30. Patients were also tested with the measurement instrument Expanded Disability Status Scale (EDSS) [ 4 ]⁠ for assessing disability of people with MS to estimate the degree of neurological impairment by means of functional system grades and sensory/blowel&bladder system grades (0.0 normal – 9.5 high disability). The inclusion criteria were: 1. no visual disorders (use of own glasses), 2. preserved function of upper extremity, 3. MMSE > = 24. Totally 23 patients were excluded from the study; 20 due to the covid-19 outbreak and 3 patients did not take psychological tests. 84 patients with disability severe enough to preclude full daily activities and are ambulatory without aid for about 100m (MMSE 27.6 ± 2.1, EDSS 5.8 ± 1.2) were enrolled and allocated to intervention in 4 groups (Fig. 2 ). The enrolled participants were randomized into 4 groups by computer random generator to get equal number of participants per group. All participants received the same amount of therapy and followed the same study protocol, but used the exergame with different types of virtual cubes: group G1: small and bouncing cubes (N = 20, age 53.8 ± 10.1 years, MMSE 26.4 ± 2.6, EDSS 5.8 ± 1.2) group G2: small and non-bouncing cubes (N = 21, age 53.6 ± 11.5 years, MMSE 27.6 ± 2.9, EDSS 6.0 ± 1.2) group G3: big and bouncing cubes (N = 22, age 48.6 ± 12.8 years, MMSE 27.8 ± 1.4, EDSS 6.1 ± 0.8) group G4: big and non-bouncing cubes (N = 21, age 51.2 ± 11.8 years, MMSE 28.5 ± 1.2, EDSS 5.6 ± 1.4) The study was approved by local ethics committee and all participants voluntarily provided a written consent. Participants could withdraw anytime without providing a reason. Figure 2 . about here. 2.4 Research protocol The participants were seated in front of the table with laptop computer. The camera was placed on a table in front of the participant to cover the optimal working space (Fig. 1 ). An additional support for the participant’s arm would be provided if needed. The participants were requested to pick the virtual cubes with the more affected hand and place them in the open treasure box (Fig. 1 ). The cubes virtual model (size, weight, material, bouncing factor) was defined selectively for each group and was equal for all members of the group. The task was the same for all groups regardless of the virtual cube size and bounciness; the participant picked and placed the cubes one by one into the open chest within 120 s. The cube disappeared, when properly dropped in the chest. If all 10 cubes are successfully relocated before the time expires, then the task would be considered accomplished. The exergame started with 10 cubes randomly spread over the virtual environment. Each participant took 10 training sessions throughout the three weeks. Each session lasted less than 30 min. allowing the participants 5 full time trials. Short 1–2 min. breaks were taken between the trials. All participants voluntarily fulfilled the modified Intrinsic Motivation Inventory (IMI) [ 13 ]⁠ immediately after each session [ 10 ]⁠. All participants took the functional test Box & Blocks Test (BBT) [ 14 ]⁠ before and after the treatment. Visual-spatial cognitive tests, Delis–Kaplan Executive Function System (D-KEFS) [ 15 ]⁠, Judgment of Line Orientation test (JLO), [ 16 ]⁠, [ 17 ]⁠ and Frontal Assessment Battery (FAB), [ 18 ]⁠ were performed at inpatient hospital before the treatment. 2.5 Data assessment 2.5.1 Psychological tests The visual-spatial cognitive tests, D-KEFS, JLO and FAB were carried out at inpatient hospital by the clinical psychologist before the commencement of the treatment. We used a scaled scoring for all D-KEFS sub-tests; visual scanning, number sequencing, letter sequencing, number letter switching and motor speed. It ranges from 0–19 with an average score of 10 points; scoring 16 and above would be very superior performance, between 14 and 16 superior, between 12 and 14 high average, 8–12 average, 6–8 low average, 4–6 borderline and below 4 the performance is considered impaired / mild / moderate or severe (Psychometric conversion table). Our participants also took the purely 30-item visual test JLO. Each item is scored from 0–15; 0–5 severe deficit, 6–7 moderate deficit, 8–9 mild deficit, 10 borderline and 11 + normal. For the presentation of data and statistical comparison between the groups we used the percentile rank (Psychometric conversion table); severe deficit (1), borderline (< 10), average (25–75), high average (75–90). At last the patients took the cognitive test FAB, a short cognitive and behavioral sub-test [ 19 ]⁠. The literature reported on degrees of cognitive impairments for the raw values < 10 and mean values (14.24) with standard deviation (3.43, N = 372) for the patients with MS [ 20 ]⁠. 2.5.2 Clinical functional test, Intrinsic motivation inventory and Heart Rate The BBT was carried out by a skilled occupational therapist before and after the exergaming sessions in the rehabilitation center. The BBT was the occupational therapist’s tool to evaluate unilateral gross manual dexterity. The goal was to place the wooden cubes from one to another compartment in 60 s. The score was equal to the number of relocated cubes. The participants valued their experience with the exergame immediately after the daily sessions by rating the 8 statements of the modified [ 21 ]⁠ Intrinsic Motivation Inventory (IMI) [ 22 ]⁠ using the 7-point Likert scale. The score 1 indicated a total disagreement and a score 7 a full agreement with the particular statement. The statements were afterward classified into 4 categories: Interest/Enjoyment statement 3: The game seemed very interesting to me. statement 7: Playing was fun. Effort/Importance statement 1: I have made a lot of efforts to play the game statement 4: I did my best. Perceived Competence statement 2: I think it's a good game for me. statement 6: I am satisfied with my result. Pressure/Tension statement 5: During the playing I was very tense. statement 8: During the game I felt under pressure. Each category presented the IMI measure scale ranging between 2 and 14 points. During the exergaming sessions a heart rate was constantly monitored at the wrist of the participant using a smart bracelet (Samsung Galaxy Fit-e). 2.5.3 Kinematics of the hand Objective parameters for the evaluation of a neuro motor deficiencies in upper extremity exergaming were developed [ 23 ]⁠ and used in patients with Parkinson’s disease [ 10 ]⁠. The pose of the palm and fingers were assessed with the LMC and transformed into the base coordinate system. The kinematics of the hand (Figure ) and time were used to calculate the total time of manipulation of all virtual cubes (TtoM), average time of manipulation of each virtual cube (AToM), number of successfully inserted boxes (IN), total number of tries (TNoT), time from the first touch of the virtual cube to the end of the game (TfFTtE), average shortest kinematic distance and average tremor indicator (ATI) [ 23 ]⁠. The time from the first touch with a virtual cube until the last cube was placed in the chest was considered the total time of the trial unless the user did not accomplish the task. In the current study we have focused on the major indicators of time and game score, i.e. AToM, TfFTtE, IN and TNoT. We also report on the ATI as it is expected to be much larger with smaller cubes. Figure 3 . about here. 2.6 Data analysis Matlab (MathWorks, Natick MA, USA) was used to extract raw kinematic data from the data stream of the LMC. We calculated the position of the palm and use it to calculate of movements in time and space. Mean values were calculated for all kinematic parameters for each group and sorted by the chronological sessions. Additionally we made the same analysis for the manipulation of the virtual cubes. For the presentation purposes we used a 4th order polynomial curve fitting with normalization. The data were unbalanced therefore the equivalent of the Friedman’s test, the Mac-Skilling non-parametric test was used [ 24 ]⁠. The significance level was set to p = 0.05. The Matlab Statistical Toolbox was used to calculate the mean; standard deviation, Levene’s test, Analysis of variance (ANOVA) were used to examine the differences between the groups, Kruskal–Wallis one-way analysis of variance reported on group effects in psychological tests and the Friedman 2-way non-parametric test for unbalanced data hypothesis check for the group effect in the BBT, HR and the IMI. The significance level was set to p = 0.05. Cohen’s U3 index [ 25 ]⁠ was used to find effect sizes in BBT, IMI, kinematic and exergame parameters. The U3 defines the proportion of data from the specific group that were smaller than the median values of the other group. There was no effect at U3 = 0.5 and maximal at 0 when all group data were above the median of the other group or 1 when all group data were below the median of the compared group (effect size: small 0.4/0.6, medium 0.3/0.7, and large 0.2/0.8). The Matlab Statistical Toolbox (MathWorks, Natick MA, USA) with the Measures of Effect Size (MES) Toolbox [ 26 ]⁠ and GNU PSPP (Free Software Foundation, Inc., Boston MA, USA) were used for analysis. 3 Results 3.1 Psychological differences between the groups 2 participants (1 from group G2 and 1 from group G4) did not accomplished all daily sessions. Therefore in total 82 participants’ data was used for computation. No significant statistical differences between the participating groups were found in age, gender and the EDSS with Levene’s test and ANOVA, but in the MMSE (Table 1 ) the Kruskal–Wallis non-parametric test demonstrated noticeable differences between the group 1 and 4. Table 1 Mean differences between the groups. variable Group (mean/SD) Levene’s Test ANOVA / Kruskal Walilis Test G1 G2 G3 G4 (F/p) (p-value) Gender (M/F) 5/15 8/12 5/17 5/15 1.64/0.187 0.604 Age (mean/SD) 53.8/10.8 53.6/11.5 48.6/12.8 49.1/11.8 0.18/0.907 0.350 EDSS 5.8/1.2 6.0/1.2 6.1/0.8 5.6/1.4 1.56/0.206 0.550 MMSE 26.4/2.6 27.6/2.9 27.8/1.4 28.5/1.2 3.95/0.012* 0.056* Standardized higher level cognitive functions test, the Delis-Kaplan Executive Function System (D-KEFS) demonstrated average (8–12 scaled score) to low-average (5–7 scaled score) mean performance in visual scanning, number sequencing, average in letter sequencing and number letter switching and average to high-average (12 + scaled score) performance in motor speed functions (Fig. 4 ). Statistically no significant differences were found between the groups in all D-KEFS subtests (p = 0.3376, p = 0.743, p = 0.9887, p = 0.9083, p = 0.4365, respectively). All participants across the groups were cognitively non-impaired, having the FAB higher than 10 (15.9 / 2.3) [ 20 ]⁠. There were no statistically significant differences found between the groups (p = 0.1205). The measure of visual-spatial perception (JLO) reports on average (25–75) to high-average (75–90) rank (mean 62.1 / 26.2), also without statistically significant differences between the groups (p = 0.3813). Figure 4 . about here. 3.2 Clinical outcomes and intrinsic motivation The mean value of the BBT increased from 48.45 SD 8.98 to 50.75 SD 9.86 cubes in the G1 group, 42.64 SD 11.47 to 47.18 SD 11.41 cubes in the G2 group,47.50 SD 7.93 to 52.04 SD 9.28 cubes in the G3 group and 41.38 SD 14.60 to 47.45 SD 13.76 cubes for the affected hand in the G4 group after the sessions. The (Fig. 5 ) shows the median values, the 25th and 75th percentile and the whiskers 1.5 times the interquartile range. The effect sizes are presented with Cohen’s U3 and 95% confidence interval (CI): U3 = 0.7 CI [0.35–0.9], U3 = 0.7 CI [0.4–0.9], U3 = 0.8 CI [0.5–0.98],and U3 = 0.6 CI [0.33–0.85] for the G1, G2, G3 and for the G4 group, respectively. The Levene’s test for homogeneity of variances rejected the hypothesis (3.41, p = 0.022), and the Friedman 2-way test did not confirm statistically significant differences between the groups (χ 2 = 4.099, p = 0.2509). Figure 5 . about here All participating groups demonstrated substantially significant differences between the 1st and the last session (Table 2 ); for the “interest/enjoyment” and “perceived competence” measure scales of the IMI. However, the differences between the groups were statistically insignificant (p = 0.978). All groups but G1 demonstrated substantial differences (U3) effort/importance and “pressure/tension” measure scales. The group G1 expressed neglectable changes in the “effort/importance” and “pressure/tension” (U3 = 0.4). Table 2 The Cohen’s U3 coefficient demonstrated substantial differences in effect size between 1st and last session for IMI measure scales. Group G1 Group G2 Group G3 Group G4 Cohen's U3 [CI] Cohen's U3 [CI] Cohen's U3 [CI] Cohen's U3 [CI] Friedman session 1 vs 10 session 1 vs 10 session 1 vs 10 session 1 vs 10 p Interest / Enjoyment 0.3 [0.1–0.8] 0.2 [0.0-0.8] 0.8 [0.3–0.9] 0.8 [0.15–0.9] 0.978 Effort / Importance 0.4 [0.13–0.85] 0.2 [0.0-0.75] 0.9 [0.35–0.95] 0.7 [0.35–0.85] 0.216 Perceived competence 0.6 [0.4–0.9] 0.8 [0.5-1.0] 0.9 [0.68-1.0] 0.8 [0.38-1.0] 0.860 Pressure / Tension 0.4 [0.1–0.7] 0.2 [0.0-0.65] 0.1 [0.05–0.45] 0.1 [0.0-0.5] 0.297 *statistically significant differences (p < 0.05) The Cohen’s U3 coefficient demonstrated substantial differences in effect size between 1st and last session for IMI measure scales. Group G4 had constantly lower heart rate (HR) during the exergaming session (81.5 SD 1.0 bpm) than the other groups, also significantly lower than in other groups (χ 2 = 7.798, p = 0.050). The HR was in average the highest in the group G2 (88.1 SD 2.0 bpm) which also experienced the highest pressure/tension (Figure ). The average HR was lower in G1 (85.8 SD 0.9 bpm), but the pressure/tension was rather high throughout the sessions. Figure 6 . about here 3.3 Kinematics of the hand at exergaming The participants of the group 1 had the most difficult task with small and bouncing cubes, therefore the longest total time of manipulation TtoM and TfFTtE were substantially higher, up to 25%. Furthermore the AToM indicated longer time, in particular at the finish of the sessions when the participants paid attention on accuracy and success in exergaming. Indeed, all groups were more successful, participants being able to insert more cubes and reducing the TNoT. The average shortest distance was rather constantly rising adequately for all groups. Members of the group 4 managed to reduce the time of manipulation and the TfFTtE, followed by higher successful rate in inserting cubes in minimal number of tries. The ATI was larger in manipulation of small objects (Fig. 7 ). Figure 7 . about here Participants of the group 1 hardly managed to insert in average 8 cubes in 120s with the AToM between 1.7 and 1.9 s and keeping the HR at 85.7 SD 0.9 bpm. The TfFTtE was the highest among all groups in average 100s at 7 inserted cubes and 89 s at 8 inserted cubes (Figure ). Participants of the group 4 were successful at exergaming, placing all the 10 cubes and significantly decreasing the TfFTtE from 87 s (8 cubes) to 63 s (10 cubes) at low HR at 81.5 SD 1.0 bpm. Also their AToM was the lowest among the groups. Participants of the groups 2 and 3 decreased the TfFTtE from 98 s to 67 s or 93 s to 63 s, respectively to achieve higher exergaming score. But with higher HR, 88.1 SD 2.0 and 86.6 SD 1.9, respectively. The AToM was lower than in the group 1, but higher than in the group 4. Participants of the group 3 were in average more successful in exergaming than group 2 (9.6 vs 9.1 cubes). Statistically significant differences (p < 0.05) in time related actions, exergame performance and tremor index were found between the groups at 1st and the last session (Table ). Table 3 The mean outcomes of the TfFTtE (Time from first touch to the end), AToM (Average time of manipulation), IN (Inserted boxes), TNoT (Total number of tries) and ATI (Average tremor indicator) at 1st and last session. The Mac-Skilling non-parametric test was used to test the statistical differences (group x time, p < 0.05). Cohen’s U3 demonstrated the size effect between 1st and 10th session. Group G1 Cohen’s U3 Group G2 Cohen’s U3 Group G3 Cohen’s U3 GroupG4 Cohen’s U3 Mac-Skilling 1st 10th U3 1st 10th U3 1st 10th U3 1st 10th U3 p mean sd mean sd [CI] mean sd mean sd [CI] mean sd mean sd [CI] mean sd mean sd [CI] TfFTtE 100.4 20.9 88.9 28.2 0.3 [0.05–0.7] 98.9 15.1 67.9 27.5 0.0 [0.0-0.15] 93.8 24.1 63.6 23.3 0.15 [0.0-0.3] 87.5 22.6 63.4 25.8 0.14 [0-0.4] 0.0027* AToM 1.72 0.82 1.90 0.47 0.6 [0.5–0.9] 1.44 0.55 1.40 0.45 0.45 [0.2–0.8] 1.59 0.67 1.35 0.35 0.4 [0.2–0.7] 1.43 0.58 1.34 0.49 0.5 [0.1–0.8] 0.0081* IB 7.05 2.24 7.95 2.33 0.76 [0.4–0.9] 7.23 1.99 9.17 1.35 0.95 [0.8-1.0] 7.41 2.35 9.57 0.67 0.9 [0.5–0.9] 8.08 2.51 9.68 0.83 0.7 [0.5–0.9] 0.0038* TNoT 17.0 5.56 14.1 1.77 0.43 [0.2–0.6] 17.9 6.51 14.5 4.2 0.15 [0.0-0.6] 14.6 3.49 14.3 3.80 0.35 [0.15–0.8] 14.5 5.40 13.72 3.93 0.2 [0.05–0.6] 0.1308 ATI 11.9 7.06 11.9 3.89 0.7 [0.3–0.9] 8.60 3.05 8.10 2.86 0.6 [0.15–0.6] 9.76 4.71 7.38 2.31 0.35 [0.15–0.6] 7.41 1.77 7.38 3.46 0.2 [0.05–0.8] 3.3922e-05* *statistically significant differences (p < 0.05) Figure 8 . about here Additionally, we found differences in the TfFTtE and the IB between the assessments in the 1st session and the last, 10th session, substantially significant for all the groups (Table ). 4 Discussion 4.1 Exergaming performance and functional outcomes In the study with more than hundred patients with MS the groups were almost equally randomized, demonstrating no statistically significant difference in gender, age and EDSS. There were statistically significant differences between the groups in visual-spatial or cognitive capabilities, but no patient's score was bellow the required MMSE value. The visual-spatial test JLO and cognitive and short behavioral test FAB taken before the commencement of the sessions did not show critical or severe impairment, rather average to low average score according to age and education norms (Appollonio et al., 2005) meaning that exergaming should not present a burden. Besides, exergaming has proven effective in people with Parkinson's disease [ 27 ]⁠ and a systematic review [ 28 ]⁠ also reported on comparable outcomes of exergaming and virtual reality supported balance and gait rehabilitation with conventional training. Additionally we assume that practicing fine motor activities is important for brain excitability [ 29 ]⁠. The exergaming of fine motor activities within the performed study contributed to the substantial changes of kinematic parameters and exergame scores in all the groups. The participants evidently got familiar with the exergame and decreased the TNoT consequently achieving better score in the IB. Furthermore, they needed less time for the pick and place task, decreasing the AToM and also the TfFTtE. However, this was not the case for the group 1. Also the statistical test showed significant differences between the groups. The group 1 required more manipulation time (AToM) for each virtual cube. The task with small cubes with bouncing characteristics was confirmed to be the most difficult task. The participants in this group experienced higher HR, but they expressed high level of interest and enjoyment. On contrary the group 4 mastered the task with large and non-bouncing cubes in the first week, finishing each session faster and faster. But their interest/enjoyment rate felt in the second week. The participants of the group 4 reported on low pressure/tension and also low HR was recorded. Most of these findings are consistent with the recent studies [ 30 ]⁠, reporting on effects of cognitive load on motor performance in people with MS. The study pointed out a strong correlation of the results with the Montreal Cognitive Assessment - MoCA [ 31 ]⁠. The aforementioned study is also in line with our findings that people with MS have a strong ability to improve motor control. We reported on average improvement of the fine motor skills assessed by the BBT in all groups. However, the difference between the groups were not evident and it is difficult to determine which specific game parameter was clinically more relevant. Nevertheless, the improvement of kinematic parameters may provide an insight into the neuromotor mechanism [ 32 ]⁠ and is a good supplement to the validated clinical tests. 4.2 Suggested exergaming parameters for higher motivation Improvement of fine motor skills demonstrated by kinematic assessment may present a valuable information for researchers, but clinicians value the clinical trials with validated test more. Kinematic analysis can highlight the clinical changes in a different perspective, may reveal differences over the treatment that the clinical instrument often neglect due to sensibility [ 33 ]⁠. In the study the substantial changes (Cohen's U3) in the intrinsic motivation inventory (IMI) can be explained by the kinematic and game score analysis, particularly in interest/enjoyment and pressure/tension categories. The clinical test showed changes equally for all groups, but the IMI reported on drop of motivation and tension in all groups except group 1. The participant of group 1 handled small and bouncy virtual cubes, difficult to grasp or pinch and often fall out of the hand. The members of the groups 4 and 3 did not have such problem, the later only had to confront the bounciness of the virtual cubes. However, also the bounciness could not be neglected. We found the non-bounciness in group 2 less challenging (interest/enjoyment), but handling small virtual objects and keeping the pressure/tension and the HR high. According to our findings we may rank the difficulty level from easiest (group 4) to the most difficult (group 1). Such exergame parameters can present an important option to control the participants engagement and keep the participants motivated. We have already demonstrated promising results with intrinsic motivation inventory as a key motivation factor for participants [ 34 ]⁠. Therefore identification of optimal game parameters would be important to achieve middle term motivation for telerehabilitation and exercises at home. 4.3 Limitations of the study and future work The LMC has been validated with golden standard optical measurement systems [ 35 ] and provide clinically acceptable and meaningful outcomes [ 36 ]⁠ thus our kinematic outcomes can be considered reliable. However, we have noticed an occasional unexpected turning of the virtual hand, an unpleasant event making the pick and place task significantly longer. If such an event occurred at least twice in a single session, we would restart and repeat the session. In a case of muscle weakness we may use a passive or active dynamic arm support [ 37 ]⁠. Despite the large number of participants they were randomized into four groups leaving some space for a more extensive study. In the future we may recruit additional participants and provide solid conclusion on the correct choice of virtual object size and behavior for specific neuromuscular disease or disorder. 5 Conclusion We have demonstrated that the size and behavior of virtual objects have significant impact on functional exercises and motivation of persons with MS. The difficulty level of the task may help the patient to stay focused on the exergame, increase the effort, but consequently also the tension. Particularly the later can result in a higher heart rate. On contrary the easy task has become boring in less than a week. Both middle level options have proven as good. These findings may provide insight into kinematic strategies when using exergaming in occupational and physiotherapy. Additionally, the developers may appreciate such information when designing the complex task for comprehensive and long-term use of such applications in rehabilitation medicine, in particular telerehabilitation. Declarations Ethics approval and consent to participate The study (Approval Number: URIS202001) was approved by ethics committee of University Rehabilitation Institute, Republic of Slovenia and all participants provided an informed written consent. The procedure was in accordance with the principles of the Declaration of Helsinki on biomedical research on human beings, the provisions of Council of Europe Convention on the Protection of Human Rights and Dignity of the Human Being with regard to the Application of Biology and Medicine (Oviedo Convention) and the principles of Slovenian Code of medical ethics. The authors confirm that all ongoing and related trials for this drug/intervention are registered (ClinicalTrials.gov Identifier: NCT04266444, 12/02/2020, https://clinicaltrials.gov/ct2/show/NCT04266444). Consent for publication All authors, project group members and participant agreed on publication. Participant provided a written consent for the publication of photographs. Availability of data and material Anonymized data generated or analyzed during this study are available on request. Competing interests The authors declare that they have no competing interests Funding Slovenian Research Agency (research core funding No. P2-0228). Health Insurance Institute of Slovenia. Authors' contributions All authors read and approved the final manuscript. Acknowledgements The authors would like to thank Klemen Grabljevec, MD, MSc for medical advices, Dejana Zajc, OT, Marta Vidmar, OT, Polonca Rogelj OT, Katja Perme Sušnik, OT, Gabriela Češarek Vučko, OT for assistance with patients and the psychologists Tara Klun, Marjana Kranj Dobre and dr. Urša Čižman Štaba for providing psychological outcomes. The authors also acknowledge the financial support from the Slovenian Research Agency (research core funding No. P2-0228) and the Health Insurance Institute of Slovenia. References Hinrichs J, Finlayson M. - An Overview of Multiple Sclerosis Rehabilitation. Mult Scler Rehabil [Internet]. CRC Press; 2012 [cited 2022 May 27];66–91. Available from: https://www.taylorfrancis.com/chapters/edit/10.1201/b12666-9/overview-multiple-sclerosis-rehabilitation-jutta-hinrichs-marcia-finlayson Cameron M, Finlayson M, Kesselring J. - Multiple Sclerosis Basics. Mult Scler Rehabil [Internet]. CRC Press; 2012 [cited 2022 May 27];32–57. Available from: https://www.taylorfrancis.com/chapters/edit/10.1201/b12666-7/multiple-sclerosis-basics-michelle-cameron-marcia-finlayson-jürg-kesselring Henze T. Recommendations on Rehabilitation Services for Persons with Multiple Sclerosis in Europe endorsed by RIMS, Rehabilitation in Multiple Sclerosis European Multiple Sclerosis Platform (EMSP). Eur Mult Scler Platf. 2012; Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology [Internet]. Neurology; 1983 [cited 2022 Mar 17];33:1444–52. Available from: https://pubmed.ncbi.nlm.nih.gov/6685237/ Kister I, Chamot E, Salter AR, Cutter GR, Bacon TE, Herbert J. Disability in multiple sclerosis: a reference for patients and clinicians. Neurology [Internet]. Neurology; 2013 [cited 2022 Apr 19];80:1018–24. Available from: https://pubmed.ncbi.nlm.nih.gov/23427319/ Bertoni R, Lamers I, Chen CC, Feys P, Cattaneo D. Unilateral and bilateral upper limb dysfunction at body functions, activity and participation levels in people with multiple sclerosis. Mult Scler [Internet]. Mult Scler; 2015 [cited 2022 Apr 19];21:1566–74. Available from: https://pubmed.ncbi.nlm.nih.gov/25662346/ Simmons RD. Life issues in multiple sclerosis. Nat Rev Neurol [Internet]. Nat Rev Neurol; 2010 [cited 2022 Apr 19];6:603–10. Available from: https://pubmed.ncbi.nlm.nih.gov/20856267/ Goverover Y, Genova HM, DeLuca J, Chiaravalloti ND. Impact of multiple sclerosis on daily life. Chang Brain Impact Dly Life [Internet]. Springer New York; 2016 [cited 2022 Apr 19];145–65. Available from: /record/2016-62114-007 Massetti T, Trevizan I, Arab C, Favero F, Ribeiro-Papa D, de Mello Monteiro C. Virtual reality in multiple sclerosis - A systematic review. Mult Scler Relat Disord [Internet]. Mult Scler Relat Disord; 2016 [cited 2021 Jul 8];8:107–12. Available from: https://pubmed.ncbi.nlm.nih.gov/27456884/ Cikajlo I, Peterlin Potisk K. Advantages of using 3D virtual reality based training in persons with Parkinson’s disease: A parallel study. J Neuroeng Rehabil [Internet]. BioMed Central Ltd.; 2019 [cited 2019 Dec 10];16:119. Available from: https://pubmed.ncbi.nlm.nih.gov/31623622/ Webster A, Poyade M, Rooney S, Paul L. Upper limb rehabilitation interventions using virtual reality for people with multiple sclerosis: A systematic review [Internet]. Mult. Scler. Relat. Disord. Mult Scler Relat Disord; 2021 [cited 2021 Jul 8]. Available from: https://pubmed.ncbi.nlm.nih.gov/33212400/ Guna J, Jakus G, Pogačnik M, Tomažič S, Sodnik J. An Analysis of the Precision and Reliability of the Leap Motion Sensor and Its Suitability for Static and Dynamic Tracking. Sensors [Internet]. Multidisciplinary Digital Publishing Institute; 2014 [cited 2017 Feb 17];14:3702–20. Available from: http://www.mdpi.com/1424-8220/14/2/3702/ McAuley E, Duncan T, Tammen V V. Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: a confirmatory factor analysis. Res Q Exerc Sport. 1989;60:48–58. Mathiowetz V, Volland G, Kashman N, Weber K. Adult norms for the Box and Block test of manual dexterity. Am J Occup Ther. 1985;39:386–91. Delis DC, Kaplan E, Kramer JH. Delis-Kaplan Executive Function System: Examiner’s manual. San Antonio, TX: The Psychological Corporation; 2001. Benton A, Varney N, Hamsher K. Visuospatial judgment. A clinical test. Arch Neurol [Internet]. Arch Neurol; 1978 [cited 2021 Jul 8];35:364–7. Available from: https://pubmed.ncbi.nlm.nih.gov/655909/ Moore B, Denckla M. Neurofibromatosis. In: Yeates KO, Ris MD, editors. Pediatr Neuropsychol Res Theory, Pract. New York, New York, USA: Guilford Press; 1999. p. 149–70. Dubois B, Slachevsky A, Litvan I, Pillon B. The FAB: a Frontal Assessment Battery at bedside. Neurology [Internet]. Neurology; 2000 [cited 2021 Jul 8];55:1621–6. Available from: https://pubmed.ncbi.nlm.nih.gov/11113214/ Appollonio I, Leone M, Isella V, Piamarta F, Consoli T, Villa ML, et al. The frontal assessment battery (FAB): Normative values in an Italian population sample. Neurol Sci. 2005;26:108–16. Brown RG, Lacomblez L, Landwehrmeyer BG, Bak T, Uttner I, Dubois B, et al. Cognitive impairment in patients with multiple system atrophy and progressive supranuclear palsy. Brain [Internet]. Oxford Academic; 2010 [cited 2022 Apr 25];133:2382–93. Available from: https://academic.oup.com/brain/article/133/8/2382/388829 Colombo R, Pisano F, Mazzone A, Delconte C, Micera S, Carrozza MC, et al. Design strategies to improve patient motivation during robot-aided rehabilitation. J Neuroeng Rehabil. 2007;4. McAuley E, Duncan T, Tammen V V. Psychometric Properties of the Intrinsic Motivation Inventory in a Competitive Sport Setting: A Confirmatory Factor Analysis. Res Q Exerc Sport [Internet]. 1989 [cited 2019 Feb 13];60:48–58. Available from: http://www.ncbi.nlm.nih.gov/pubmed/2489825 Cikajlo I, Pogačnik M. Movement analysis of pick-and-place virtual reality exergaming in patients with Parkinson’s disease. Technol Health Care [Internet]. NLM (Medline); 2020 [cited 2020 Aug 25];28:391–402. Available from: https://pubmed.ncbi.nlm.nih.gov/32200361/ Skillings JH, Mack GA. On the Use of a Friedman-Type Statistic in Balanced and Unbalanced Block Designs. Technometrics [Internet]. 1981 [cited 2019 Feb 14];23:171–7. Available from: http://www.tandfonline.com/doi/abs/10.1080/00401706.1981.10486261 Cohen J. Statistical power analysis for the behavioral sciences. Academic Press; 1977. Hentschke H, Stüttgen MC. Computation of measures of effect size for neuroscience data sets. Eur J Neurosci [Internet]. 2011 [cited 2019 Apr 2];34:1887–94. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22082031 Yuan RY, Chen SC, Peng CW, Lin YN, Chang YT, Lai CH. Effects of interactive video-game-based exercise on balance in older adults with mild-to-moderate Parkinson’s disease. J Neuroeng Rehabil. BioMed Central; 2020;17. Casuso-Holgado MJ, Martín-Valero R, Carazo AF, Medrano-Sánchez EM, Cortés-Vega MD, Montero-Bancalero FJ. Effectiveness of virtual reality training for balance and gait rehabilitation in people with multiple sclerosis: a systematic review and meta-analysis. Clin Rehabil. SAGE Publications Ltd; 2018;32:1220–34. Lulic T, El-Sayes J, Fassett HJ, Nelson AJ. Physical activity levels determine exercise-induced changes in brain excitability. Antal A, editor. PLoS One [Internet]. Public Library of Science; 2017 [cited 2019 Feb 4];12:e0173672. Available from: https://dx.plos.org/10.1371/journal.pone.0173672 Al-Sharman A, Khalil H, El-Salem K, Alghwiri AA, Khazaaleh S, Khraim M. Motor performance improvement through virtual reality task is related to fatigue and cognition in people with multiple sclerosis. Physiother Res Int [Internet]. Physiother Res Int; 2019 [cited 2021 Jul 8];24. Available from: https://pubmed.ncbi.nlm.nih.gov/31120581/ Dagenais E, Rouleau I, Demers M, Jobin C, Roger E, Chamelian L, et al. Value of the MoCA test as a screening instrument in multiple sclerosis. Can J Neurol Sci. 2013;40:410–5. Maier M, Ballester BR, Verschure PFMJ. Principles of Neurorehabilitation After Stroke Based on Motor Learning and Brain Plasticity Mechanisms [Internet]. Front. Syst. Neurosci. Frontiers Media S.A.; 2019 [cited 2021 Jan 6]. p. 74. Available from: www.frontiersin.org Johansson GM, Grip H, Levin MF, Häger CK. The added value of kinematic evaluation of the timed finger-to-nose test in persons post-stroke. J Neuroeng Rehabil [Internet]. BioMed Central Ltd.; 2017 [cited 2022 May 12];14:1–12. Available from: https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-017-0220-7 Gorsic M, Cikajlo I, Novak D, Goršič M, Cikajlo I, Novak D. Competitive and cooperative arm rehabilitation games played by a patient and unimpaired person: effects on motivation and exercise intensity. J Neuroeng Rehabil [Internet]. 2017 [cited 2018 Oct 1];14:23. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28330504 Niechwiej-Szwedo E, Gonzalez D, Nouredanesh M, Tung J. Evaluation of the Leap Motion Controller during the performance of visually-guided upper limb movements. PLoS One [Internet]. Public Library of Science; 2018 [cited 2022 May 10];13:e0193639. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0193639 Smeragliuolo AH, Hill NJ, Disla L, Putrino D. Validation of the Leap Motion Controller using markered motion capture technology. J Biomech [Internet]. J Biomech; 2016 [cited 2022 May 10];49:1742–50. Available from: https://pubmed.ncbi.nlm.nih.gov/27102160/ Van Der Heide LA, Van Ninhuijs B, Bergsma A, Gelderblom GJ, Van Der Pijl DJ, De Witte LP. An overview and categorization of dynamic arm supports for people with decreased arm function [Internet]. Prosthet. Orthot. Int. SAGE Publications Ltd; 2014 [cited 2020 Sep 4]. p. 287–302. Available from: https://research.tue.nl/en/publications/an-overview-and-categorization-of-dynamic-arm-supports-for-people Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 2 posted Editorial decision: Major revision 04 Oct, 2022 Reviews received at journal 04 Oct, 2022 Reviewers agreed at journal 19 Sep, 2022 Reviews received at journal 13 Sep, 2022 Reviewers agreed at journal 09 Sep, 2022 Reviewers invited by journal 02 Aug, 2022 Editor assigned by journal 02 Aug, 2022 Editor invited by journal 25 Jun, 2022 Submission checks completed at journal 25 Jun, 2022 First submitted to journal 09 Jun, 2022 You are reading this latest preprint version Show more versions 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. We do this by developing innovative software and high quality services for the global research community. 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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-1707133","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[{"code":1,"date":"2022-06-02 15:01:30","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}}],"articleType":"Article","associatedPublications":[],"authors":[{"id":119312200,"identity":"19e688c1-d661-4432-96a9-9b993a9a7db9","order_by":0,"name":"Imre Cikajlo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIie2PvQrCMBRGbyjURewmFyr0FVIK2sGHiUtdOgiuohHBSXAtCD5LQ8DNvZNUfIG6dXAw8WdtOgrmLCHhntzvA7BYfhD3fSAFkBwq+nlm7RTBSdZG+aJmCXe6bYL1+udrCYs48tZifRvPLjDa505VNgXzpxGFEw4xF5sopXMYFMzFpmCun7hIOI4hF1s/pWyVoSpoUDq1VgKtxJQBeiqYaYsqjkOqFdCKWmEK5iA7YRSqLuFOKzjZNirBISFVtViGx0KKsn7oYFLe6wblxetPzL9Xwk3CB6/toMVisfwdT0S0Qz82UWsoAAAAAElFTkSuQmCC","orcid":"","institution":"Univerzitetni Rehabilitacijski Inštitut","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Imre","middleName":"","lastName":"Cikajlo","suffix":""},{"id":119312201,"identity":"c14a72e6-1323-416d-85c2-e490059547ab","order_by":1,"name":"Alma Hukić","email":"","orcid":"","institution":"Univerzitetni Rehabilitacijski Inštitut","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Alma","middleName":"","lastName":"Hukić","suffix":""},{"id":119312202,"identity":"90152490-7a87-4e40-bd8e-5b81bbcc80ee","order_by":2,"name":"Anja Udovčić Pertot","email":"","orcid":"","institution":"Univerzitetni Rehabilitacijski Inštitut","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Anja","middleName":"Udovčić","lastName":"Pertot","suffix":""}],"badges":[],"createdAt":"2022-05-30 08:59:15","currentVersionCode":2,"declarations":"","doi":"10.21203/rs.3.rs-1707133/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-1707133/v2","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":23640444,"identity":"20c67de3-ed9d-44e5-a176-e8caeb6b1387","added_by":"auto","created_at":"2022-07-08 16:19:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":11498617,"visible":true,"origin":"","legend":"\u003cp\u003eExergaming setup. Ultraleap infrared camera detect the hand and finger movements for the interaction with the virtual environment. Small and big cubes with different bouncing characteristics were used to define 4 variations of the exergame.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1707133/v2/98b50990431d63dea4bbbb86.png"},{"id":23637567,"identity":"e3ce2ee1-6911-43f0-bec0-41222144cfb5","added_by":"auto","created_at":"2022-07-08 15:59:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":70202,"visible":true,"origin":"","legend":"\u003cp\u003eCONSORT Flow Diagram\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1707133/v2/c4b73f0cd9ee5e18375afca0.png"},{"id":23637570,"identity":"71054200-6893-45da-b57c-4fbe9f312513","added_by":"auto","created_at":"2022-07-08 15:59:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1275976,"visible":true,"origin":"","legend":"\u003cp\u003eTracking of the hand/palm with LMC provided trajectories in the base coordinate system enabling the calculation of the shortest distance, AToM, TNoT and the effective time of the exergame\u0026nbsp;TfFTtE. The average tremor indicator (ATI) was identified from the jagged curve.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1707133/v2/4b7938eabe598f9b7767f2d7.png"},{"id":23638219,"identity":"40a58493-fd03-4805-a81f-1e9d9ff9fcd9","added_by":"auto","created_at":"2022-07-08 16:04:29","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":374638,"visible":true,"origin":"","legend":"\u003cp\u003eD- KEFS, JLO, FAB cognitive tests demonstrated rather small differences of median values between the groups and low average to high average score, meaning that participants were cognitively not severely impaired.\u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-1707133/v2/976dad0f468f61ef8426035d.png"},{"id":23639518,"identity":"7d3c2720-ed7f-44f3-9e49-09b44cf525fc","added_by":"auto","created_at":"2022-07-08 16:14:30","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":197681,"visible":true,"origin":"","legend":"\u003cp\u003eAll participants improved their BBT score (Cohen's U3), however no statistically significant differences between the groups were found (c\u003csup\u003e2\u003c/sup\u003e = 4.099, p = 0.2509).\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-1707133/v2/d507534ae9502ddb2d14d034.png"},{"id":23638221,"identity":"2b75c0e0-83b1-4445-bffd-1ef8336835b5","added_by":"auto","created_at":"2022-07-08 16:04:30","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":660213,"visible":true,"origin":"","legend":"\u003cp\u003eParticipants of the group 1 were very much interested in the exergame, maintaining hogh level of perceived competence and effort on the expense of constant pressure/tension and high HR. On contrary the participants of the group 4 were loosing the enjoyment due to the simplicity of the task. Also much less pressure/tension was required at lower HR to accomplish the task successfully.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-1707133/v2/5aad9bd299a0fc701f3e21fa.png"},{"id":23638904,"identity":"670327f1-b8af-4dd1-8f16-df08eed0d4c9","added_by":"auto","created_at":"2022-07-08 16:09:30","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":642144,"visible":true,"origin":"","legend":"\u003cp\u003eThe kinematic and exergame parameters demonstrated that group 1 (the most difficult task with small bouncing cubes) required more time to finish the task with less success (lower number of inserted boxes). On contrary the members of the group 4 learned to manipulate the larger cubes faster and accomplished the exergames with all 10 inserted cubes after 10 sessions.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-1707133/v2/6def8562c7e85ad525279ecd.png"},{"id":23637574,"identity":"95f9121f-f6c4-4930-8593-ceca4134dc0b","added_by":"auto","created_at":"2022-07-08 15:59:30","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":436400,"visible":true,"origin":"","legend":"\u003cp\u003eThe TfFTtE was substantially lower only in groups (3, 4) that managed to accomplish the task with 9 or even 10 inserted cubes. However, obviously was not easy for the group 3 with much higher HR. The AToM was again shorter in group 4 at lower HR and much higher in group 1 with high HR.\u003c/p\u003e","description":"","filename":"Figure8.png","url":"https://assets-eu.researchsquare.com/files/rs-1707133/v2/2294363e76454b2687c99771.png"},{"id":23640445,"identity":"549dfe77-328c-4f0e-bff5-b29516eade28","added_by":"auto","created_at":"2022-07-08 16:19:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":461961,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1707133/v2/00d44ae8-593b-4fe5-a049-963efd2e673b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Size and Behavior of Virtual Objects have influence on Functional Exercise and Motivation of Persons with Multiple Sclerosis: a randomized study","fulltext":[{"header":"1 Background","content":"\u003cp\u003eMultiple sclerosis (MS) is a demyelinating disease that affects brain and spinal cord (central nervous system). The MS typically strikes in young adulthood, it is chronic and progressive, and it has a variable and unpredictable course [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]⁠. The disease is considered an autoimmune disease, attacking the cover of the nerve fibers (myelin) and causing malfunctioning of connections between the brain and the spinal cord. Consequently the \u0026ldquo;message\u0026rdquo; in the nerve is obstructed, often blocked. This results in a partial or complete loss of functionalities of daily living; vision problems, speech, aphasia, balance, coordination, fatigue, concentration, bowel \u0026amp; bladder function, functional movement disorders, etc. The disease may lead to a permanent disability. Despite the cause of the MS is not entirely known and no cure has been formally introduced, a management of the symptoms is essential in optimizing participation and quality of life in people with MS. Medications are available to address most of the symptoms [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]⁠ and can change the course of the disease to the certain level.\u003c/p\u003e \u003cp\u003eCare for people with MS should be interdisciplinary. The rehabilitation team consists of a specialist in physical and rehabilitation medicine, a nurse, a physiotherapist, an occupational therapist, a speech and language therapist, a psychologist and a social worker. The team may invite also a dietitian and a prosthetic/orthotics engineer if necessary. Together with the patient the team members define short- and long-term rehabilitation goals, rehabilitation plan and interventions, and monitor and adjust the goals and programmes according to the patient's needs and the stage of the disease [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]⁠. The effects of the rehabilitation programmes are most commonly estimated by patients' progress on the Expanded Disability Status Scale (EDSS), [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]⁠, a method of quantifying disability in people with multiple sclerosis and monitoring changes in the level of disability over time, filled by the physician, neurologist or specialist in physical and rehabilitation medicine.\u003c/p\u003e \u003cp\u003eAmong numerous consequences of MS the upper limb dysfunction is very common and often caused by a tremor, sensory deficits, weakness or loss of dexterity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]⁠, [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]⁠. Loss of motor skills affects activities of daily living (ADL), quality of life and employment status [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]⁠, [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]⁠. The clinicians and researchers have been actively developing neuromotor treatments that would effectively restore upper limb functions, raise quality of life and improve prognosis in patients with MS. The neuromotor rehabilitation of patients with MS requires several types of exercises. Virtual reality (VR) and exergaming have been suggested as potential tools [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]⁠. Several studies successfully applied non-immersive equipment, rarely reported on advantages of fully immersive equipment [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]⁠ and no evidence has been provided that VR approach would be superior to conventional approaches. However, there are some evidences that VR and exergaming are effective in improving motor function in upper extremities [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]⁠ and may play an important role in daily living activities. Particularly grasping and fine finger movements may present important tasks for persons with MS. Using virtual objects in exergaming has in contrast to the real world task an ability to modify the target of the desired task, change the object characteristics according to the required level or patients\u0026rsquo; visual, motor or cognitive capabilities also in real-time.\u003c/p\u003e \u003cp\u003eThe objectives of the randomized pilot study were to examine the effects of different sizes and bouncing properties of virtual objects on exergame performance, motivation and clinical outcomes at assumption that participants have had similar visual and cognitive capabilities.\u003c/p\u003e"},{"header":"2 Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design\u003c/h2\u003e \u003cp\u003eA randomized pilot study with patients with MS was designed. Participants were included in the study according to the inclusion and exclusion criteria. Baseline clinical assessment was carried out on the day when the participant was randomized into one of the four specific group. All groups participated in the post-treatment clinical assessment. Primary outcome measures were clinical tests with questionnaire results as a supplement. Exergaming and kinematic results were considered as secondary outcome measures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Rehabilitation system\u003c/h2\u003e \u003cp\u003eThe rehabilitation \u0026ndash; exergaming system is based on 3D kinematics assessed by the infrared camera system Leap Motion Controller (LMC, Ultraleap Inc. Mountain View, CA, USA) with Orion SDK. The LMC is a small 80 x 30 mm optical tracking device with 140 x 120 Deg field of view and tracking range between 10 and 60 cm. It detects hand and finger movements with adequate accuracy [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]⁠ and transfers data to the powerful computer with GPU via USB with 100Hz. The robust and reliable skeletal model has been further upgraded in Unity3D (Unity Technologies, CA, USA) and used to track the kinematics of the hand and fingers. Building a virtual model of the hand and combining its kinematics with a scenery in a virtual environment resulted in a handy exergame [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]⁠. The scenery comprises 10 cubes of various colors, but same size and an open treasure chest in the green virtual field (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The goal of the exergame was to pick and place all the cubes by virtual hand into the open chest within two minutes. Specifically for the study we implemented 2 variable parameters: the size and the material of the cubes. The material defined the bouncing characteristics of the cube, while the size of the cube matters when grabbing the object. The user was able to choose from 4 different options combining the size and the (non) bouncing material of the cubes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cem\u003eabout here\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Participants\u003c/h2\u003e \u003cp\u003e In the randomized pilot study from February 2020 to September 2021 we recruited 107 patients from the local hospital with diagnosed multiple sclerosis (37 male, 70 female, age 51.1\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5 years) eligible for the study according to the inclusion criteria. The participant were briefly screened for Mini Mental State Examination (MMSE) to assess the severity of cognitive impairment with a maximum score of 30. Patients were also tested with the measurement instrument Expanded Disability Status Scale (EDSS) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]⁠ for assessing disability of people with MS to estimate the degree of neurological impairment by means of functional system grades and sensory/blowel\u0026amp;bladder system grades (0.0 normal \u0026ndash; 9.5 high disability). The inclusion criteria were: 1. no visual disorders (use of own glasses), 2. preserved function of upper extremity, 3. MMSE\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;24. Totally 23 patients were excluded from the study; 20 due to the covid-19 outbreak and 3 patients did not take psychological tests. 84 patients with disability severe enough to preclude full daily activities and are ambulatory without aid for about 100m (MMSE 27.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1, EDSS 5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2) were enrolled and allocated to intervention in 4 groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The enrolled participants were randomized into 4 groups by computer random generator to get equal number of participants per group. All participants received the same amount of therapy and followed the same study protocol, but used the exergame with different types of virtual cubes:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003egroup G1: small and bouncing cubes (N\u0026thinsp;=\u0026thinsp;20, age 53.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1 years, MMSE 26.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6, EDSS 5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003egroup G2: small and non-bouncing cubes (N\u0026thinsp;=\u0026thinsp;21, age 53.6\u0026thinsp;\u0026plusmn;\u0026thinsp;11.5 years, MMSE 27.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9, EDSS 6.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003egroup G3: big and bouncing cubes (N\u0026thinsp;=\u0026thinsp;22, age 48.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.8 years, MMSE 27.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4, EDSS 6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003egroup G4: big and non-bouncing cubes (N\u0026thinsp;=\u0026thinsp;21, age 51.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.8 years, MMSE 28.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2, EDSS 5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e The study was approved by local ethics committee and all participants voluntarily provided a written consent. Participants could withdraw anytime without providing a reason.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. \u003cem\u003eabout here.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Research protocol\u003c/h2\u003e \u003cp\u003eThe participants were seated in front of the table with laptop computer. The camera was placed on a table in front of the participant to cover the optimal working space (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). An additional support for the participant\u0026rsquo;s arm would be provided if needed. The participants were requested to pick the virtual cubes with the more affected hand and place them in the open treasure box (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The cubes virtual model (size, weight, material, bouncing factor) was defined selectively for each group and was equal for all members of the group.\u003c/p\u003e \u003cp\u003eThe task was the same for all groups regardless of the virtual cube size and bounciness; the participant picked and placed the cubes one by one into the open chest within 120 s. The cube disappeared, when properly dropped in the chest. If all 10 cubes are successfully relocated before the time expires, then the task would be considered accomplished. The exergame started with 10 cubes randomly spread over the virtual environment.\u003c/p\u003e \u003cp\u003eEach participant took 10 training sessions throughout the three weeks. Each session lasted less than 30 min. allowing the participants 5 full time trials. Short 1\u0026ndash;2 min. breaks were taken between the trials. All participants voluntarily fulfilled the modified Intrinsic Motivation Inventory (IMI) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]⁠ immediately after each session [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]⁠.\u003c/p\u003e \u003cp\u003eAll participants took the functional test Box \u0026amp; Blocks Test (BBT) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]⁠ before and after the treatment. Visual-spatial cognitive tests, Delis\u0026ndash;Kaplan Executive Function System (D-KEFS) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]⁠, Judgment of Line Orientation test (JLO), [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]⁠, [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]⁠ and Frontal Assessment Battery (FAB), [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]⁠ were performed at inpatient hospital before the treatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data assessment\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.5.1 Psychological tests\u003c/h2\u003e \u003cp\u003eThe visual-spatial cognitive tests, D-KEFS, JLO and FAB were carried out at inpatient hospital by the clinical psychologist before the commencement of the treatment. We used a scaled scoring for all D-KEFS sub-tests; visual scanning, number sequencing, letter sequencing, number letter switching and motor speed. It ranges from 0\u0026ndash;19 with an average score of 10 points; scoring 16 and above would be very superior performance, between 14 and 16 superior, between 12 and 14 high average, 8\u0026ndash;12 average, 6\u0026ndash;8 low average, 4\u0026ndash;6 borderline and below 4 the performance is considered impaired / mild / moderate or severe (Psychometric conversion table).\u003c/p\u003e \u003cp\u003eOur participants also took the purely 30-item visual test JLO. Each item is scored from 0\u0026ndash;15; 0\u0026ndash;5 severe deficit, 6\u0026ndash;7 moderate deficit, 8\u0026ndash;9 mild deficit, 10 borderline and 11\u0026thinsp;+\u0026thinsp;normal. For the presentation of data and statistical comparison between the groups we used the percentile rank (Psychometric conversion table); severe deficit (1), borderline (\u0026lt;\u0026thinsp;10), average (25\u0026ndash;75), high average (75\u0026ndash;90).\u003c/p\u003e \u003cp\u003eAt last the patients took the cognitive test FAB, a short cognitive and behavioral sub-test [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]⁠. The literature reported on degrees of cognitive impairments for the raw values\u0026thinsp;\u0026lt;\u0026thinsp;10 and mean values (14.24) with standard deviation (3.43, N\u0026thinsp;=\u0026thinsp;372) for the patients with MS [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]⁠.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.5.2 Clinical functional test, Intrinsic motivation inventory and Heart Rate\u003c/h2\u003e \u003cp\u003eThe BBT was carried out by a skilled occupational therapist before and after the exergaming sessions in the rehabilitation center. The BBT was the occupational therapist\u0026rsquo;s tool to evaluate unilateral gross manual dexterity. The goal was to place the wooden cubes from one to another compartment in 60 s. The score was equal to the number of relocated cubes.\u003c/p\u003e \u003cp\u003eThe participants valued their experience with the exergame immediately after the daily sessions by rating the 8 statements of the modified [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]⁠ Intrinsic Motivation Inventory (IMI) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]⁠ using the 7-point Likert scale. The score 1 indicated a total disagreement and a score 7 a full agreement with the particular statement. The statements were afterward classified into 4 categories:\u003c/p\u003e \u003cp\u003eInterest/Enjoyment\u003c/p\u003e \u003cp\u003estatement 3: The game seemed very interesting to me.\u003c/p\u003e \u003cp\u003estatement 7: Playing was fun.\u003c/p\u003e \u003cp\u003eEffort/Importance\u003c/p\u003e \u003cp\u003estatement 1: I have made a lot of efforts to play the game\u003c/p\u003e \u003cp\u003estatement 4: I did my best.\u003c/p\u003e \u003cp\u003ePerceived Competence\u003c/p\u003e \u003cp\u003estatement 2: I think it's a good game for me.\u003c/p\u003e \u003cp\u003estatement 6: I am satisfied with my result.\u003c/p\u003e \u003cp\u003ePressure/Tension\u003c/p\u003e \u003cp\u003estatement 5: During the playing I was very tense.\u003c/p\u003e \u003cp\u003estatement 8: During the game I felt under pressure.\u003c/p\u003e \u003cp\u003eEach category presented the IMI measure scale ranging between 2 and 14 points.\u003c/p\u003e \u003cp\u003eDuring the exergaming sessions a heart rate was constantly monitored at the wrist of the participant using a smart bracelet (Samsung Galaxy Fit-e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.5.3 Kinematics of the hand\u003c/h2\u003e \u003cp\u003eObjective parameters for the evaluation of a neuro motor deficiencies in upper extremity exergaming were developed [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]⁠ and used in patients with Parkinson\u0026rsquo;s disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]⁠. The pose of the palm and fingers were assessed with the LMC and transformed into the base coordinate system. The kinematics of the hand (Figure ) and time were used to calculate the total time of manipulation of all virtual cubes (TtoM), average time of manipulation of each virtual cube (AToM), number of successfully inserted boxes (IN), total number of tries (TNoT), time from the first touch of the virtual cube to the end of the game (TfFTtE), average shortest kinematic distance and average tremor indicator (ATI) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]⁠.\u003c/p\u003e \u003cp\u003eThe time from the first touch with a virtual cube until the last cube was placed in the chest was considered the total time of the trial unless the user did not accomplish the task. In the current study we have focused on the major indicators of time and game score, i.e. AToM, TfFTtE, IN and TNoT. We also report on the ATI as it is expected to be much larger with smaller cubes.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. \u003cem\u003eabout here.\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Data analysis\u003c/h2\u003e \u003cp\u003eMatlab (MathWorks, Natick MA, USA) was used to extract raw kinematic data from the data stream of the LMC. We calculated the position of the palm and use it to calculate of movements in time and space. Mean values were calculated for all kinematic parameters for each group and sorted by the chronological sessions. Additionally we made the same analysis for the manipulation of the virtual cubes. For the presentation purposes we used a 4th order polynomial curve fitting with normalization. The data were unbalanced therefore the equivalent of the Friedman\u0026rsquo;s test, the Mac-Skilling non-parametric test was used [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]⁠. The significance level was set to p\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eThe Matlab Statistical Toolbox was used to calculate the mean; standard deviation, Levene\u0026rsquo;s test, Analysis of variance (ANOVA) were used to examine the differences between the groups, Kruskal\u0026ndash;Wallis one-way analysis of variance reported on group effects in psychological tests and the Friedman 2-way non-parametric test for unbalanced data hypothesis check for the group effect in the BBT, HR and the IMI. The significance level was set to p\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eCohen\u0026rsquo;s U3 index [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]⁠ was used to find effect sizes in BBT, IMI, kinematic and exergame parameters. The U3 defines the proportion of data from the specific group that were smaller than the median values of the other group. There was no effect at U3\u0026thinsp;=\u0026thinsp;0.5 and maximal at 0 when all group data were above the median of the other group or 1 when all group data were below the median of the compared group (effect size: small 0.4/0.6, medium 0.3/0.7, and large 0.2/0.8). The Matlab Statistical Toolbox (MathWorks, Natick MA, USA) with the Measures of Effect Size (MES) Toolbox [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]⁠ and GNU PSPP (Free Software Foundation, Inc., Boston MA, USA) were used for analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv class=\"Section2\" id=\"Sec13\"\u003e\n \u003ch2\u003e3.1 Psychological differences between the groups\u003c/h2\u003e\n \u003cp\u003e2 participants (1 from group G2 and 1 from group G4) did not accomplished all daily sessions. Therefore in total 82 participants\u0026rsquo; data was used for computation. No significant statistical differences between the participating groups were found in age, gender and the EDSS with Levene\u0026rsquo;s test and ANOVA, but in the MMSE (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) the Kruskal\u0026ndash;Wallis non-parametric test demonstrated noticeable differences between the group 1 and 4.\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMean differences between the groups.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003evariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003cp\u003e(mean/SD)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLevene\u0026rsquo;s Test\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eANOVA / Kruskal Walilis Test\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(F/p)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e(p-value)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (M/F)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5/15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8/12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5/17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5/15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.64/0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.604\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (mean/SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.8/10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.6/11.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.6/12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.1/11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.18/0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.350\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEDSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8/1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.0/1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.1/0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6/1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.56/0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.550\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMMSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.4/2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.6/2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.8/1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.5/1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.95/0.012*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.056*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eStandardized higher level cognitive functions test, the Delis-Kaplan Executive Function System (D-KEFS) demonstrated average (8\u0026ndash;12 scaled score) to low-average (5\u0026ndash;7 scaled score) mean performance in visual scanning, number sequencing, average in letter sequencing and number letter switching and average to high-average (12\u0026thinsp;+\u0026thinsp;scaled score) performance in motor speed functions (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Statistically no significant differences were found between the groups in all D-KEFS subtests (p\u0026thinsp;=\u0026thinsp;0.3376, p\u0026thinsp;=\u0026thinsp;0.743, p\u0026thinsp;=\u0026thinsp;0.9887, p\u0026thinsp;=\u0026thinsp;0.9083, p\u0026thinsp;=\u0026thinsp;0.4365, respectively). All participants across the groups were cognitively non-impaired, having the FAB higher than 10 (15.9 / 2.3) [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]⁠. There were no statistically significant differences found between the groups (p\u0026thinsp;=\u0026thinsp;0.1205). The measure of visual-spatial perception (JLO) reports on average (25\u0026ndash;75) to high-average (75\u0026ndash;90) rank (mean 62.1 / 26.2), also without statistically significant differences between the groups (p\u0026thinsp;=\u0026thinsp;0.3813).\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. \u003cem\u003eabout here.\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec14\"\u003e\n \u003ch2\u003e3.2 Clinical outcomes and intrinsic motivation\u003c/h2\u003e\n \u003cp\u003eThe mean value of the BBT increased from 48.45 SD 8.98 to 50.75 SD 9.86 cubes in the G1 group, 42.64 SD 11.47 to 47.18 SD 11.41 cubes in the G2 group,47.50 SD 7.93 to 52.04 SD 9.28 cubes in the G3 group and 41.38 SD 14.60 to 47.45 SD 13.76 cubes for the affected hand in the G4 group after the sessions. The (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e) shows the median values, the 25th and 75th percentile and the whiskers 1.5 times the interquartile range. The effect sizes are presented with Cohen\u0026rsquo;s U3 and 95% confidence interval (CI): U3\u0026thinsp;=\u0026thinsp;0.7 CI [0.35\u0026ndash;0.9], U3\u0026thinsp;=\u0026thinsp;0.7 CI [0.4\u0026ndash;0.9], U3\u0026thinsp;=\u0026thinsp;0.8 CI [0.5\u0026ndash;0.98],and U3\u0026thinsp;=\u0026thinsp;0.6 CI [0.33\u0026ndash;0.85] for the G1, G2, G3 and for the G4 group, respectively. The Levene\u0026rsquo;s test for homogeneity of variances rejected the hypothesis (3.41, p\u0026thinsp;=\u0026thinsp;0.022), and the Friedman 2-way test did not confirm statistically significant differences between the groups (\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;4.099, p\u0026thinsp;=\u0026thinsp;0.2509).\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e. \u003cem\u003eabout here\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eAll participating groups demonstrated substantially significant differences between the 1st and the last session (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e); for the \u0026ldquo;interest/enjoyment\u0026rdquo; and \u0026ldquo;perceived competence\u0026rdquo; measure scales of the IMI. However, the differences between the groups were statistically insignificant (p\u0026thinsp;=\u0026thinsp;0.978). All groups but G1 demonstrated substantial differences (U3) effort/importance and \u0026ldquo;pressure/tension\u0026rdquo; measure scales. The group G1 expressed neglectable changes in the \u0026ldquo;effort/importance\u0026rdquo; and \u0026ldquo;pressure/tension\u0026rdquo; (U3\u0026thinsp;=\u0026thinsp;0.4).\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe Cohen\u0026rsquo;s U3 coefficient demonstrated substantial differences in effect size between 1st and last session for IMI measure scales.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup G1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup G2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup G3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup G4\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCohen\u0026apos;s U3 [CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCohen\u0026apos;s U3 [CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCohen\u0026apos;s U3 [CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCohen\u0026apos;s U3 [CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFriedman\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esession 1 vs 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esession 1 vs 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esession 1 vs 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esession 1 vs 10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInterest / Enjoyment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3\u003c/strong\u003e [0.1\u0026ndash;0.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.2\u003c/strong\u003e [0.0-0.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.8\u003c/strong\u003e [0.3\u0026ndash;0.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.8\u003c/strong\u003e [0.15\u0026ndash;0.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.978\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEffort / Importance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4 [0.13\u0026ndash;0.85]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.2\u003c/strong\u003e [0.0-0.75]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.9\u003c/strong\u003e [0.35\u0026ndash;0.95]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.7\u003c/strong\u003e [0.35\u0026ndash;0.85]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerceived competence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.6\u003c/strong\u003e [0.4\u0026ndash;0.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.8\u003c/strong\u003e [0.5-1.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.9\u003c/strong\u003e [0.68-1.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.8\u003c/strong\u003e [0.38-1.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.860\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePressure / Tension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4 [0.1\u0026ndash;0.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.2\u003c/strong\u003e [0.0-0.65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.1\u003c/strong\u003e [0.05\u0026ndash;0.45]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.1\u003c/strong\u003e [0.0-0.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003e\u003cem\u003e*statistically significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eThe Cohen\u0026rsquo;s U3 coefficient demonstrated substantial differences in effect size between 1st and last session for IMI measure scales.\u003c/p\u003e\n \u003cp\u003eGroup G4 had constantly lower heart rate (HR) during the exergaming session (81.5 SD 1.0 bpm) than the other groups, also significantly lower than in other groups (\u0026chi;\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;7.798, p\u0026thinsp;=\u0026thinsp;0.050). The HR was in average the highest in the group G2 (88.1 SD 2.0 bpm) which also experienced the highest pressure/tension (Figure ). The average HR was lower in G1 (85.8 SD 0.9 bpm), but the pressure/tension was rather high throughout the sessions.\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e. \u003cem\u003eabout here\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec15\"\u003e\n \u003ch2\u003e3.3 Kinematics of the hand at exergaming\u003c/h2\u003e\n \u003cp\u003eThe participants of the group 1 had the most difficult task with small and bouncing cubes, therefore the longest total time of manipulation TtoM and TfFTtE were substantially higher, up to 25%. Furthermore the AToM indicated longer time, in particular at the finish of the sessions when the participants paid attention on accuracy and success in exergaming. Indeed, all groups were more successful, participants being able to insert more cubes and reducing the TNoT. The average shortest distance was rather constantly rising adequately for all groups. Members of the group 4 managed to reduce the time of manipulation and the TfFTtE, followed by higher successful rate in inserting cubes in minimal number of tries. The ATI was larger in manipulation of small objects (Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e. \u003cem\u003eabout here\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eParticipants of the group 1 hardly managed to insert in average 8 cubes in 120s with the AToM between 1.7 and 1.9 s and keeping the HR at 85.7 SD 0.9 bpm. The TfFTtE was the highest among all groups in average 100s at 7 inserted cubes and 89 s at 8 inserted cubes (Figure ). Participants of the group 4 were successful at exergaming, placing all the 10 cubes and significantly decreasing the TfFTtE from 87 s (8 cubes) to 63 s (10 cubes) at low HR at 81.5 SD 1.0 bpm. Also their AToM was the lowest among the groups.\u003c/p\u003e\n \u003cp\u003eParticipants of the groups 2 and 3 decreased the TfFTtE from 98 s to 67 s or 93 s to 63 s, respectively to achieve higher exergaming score. But with higher HR, 88.1 SD 2.0 and 86.6 SD 1.9, respectively. The AToM was lower than in the group 1, but higher than in the group 4. Participants of the group 3 were in average more successful in exergaming than group 2 (9.6 vs 9.1 cubes). Statistically significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in time related actions, exergame performance and tremor index were found between the groups at 1st and the last session (Table ).\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe mean outcomes of the TfFTtE (Time from first touch to the end), AToM (Average time of manipulation), IN (Inserted boxes), TNoT (Total number of tries) and ATI (Average tremor indicator) at 1st and last session. The Mac-Skilling non-parametric test was used to test the statistical differences (group x time, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Cohen\u0026rsquo;s U3 demonstrated the size effect between 1st and 10th session.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGroup G1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCohen\u0026rsquo;s U3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGroup G2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCohen\u0026rsquo;s U3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGroup G3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCohen\u0026rsquo;s U3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eGroupG4\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCohen\u0026rsquo;s U3\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMac-Skilling\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1st\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10th\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eU3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1st\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10th\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eU3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1st\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10th\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eU3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1st\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10th\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eU3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003esd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e[CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTfFTtE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3\u003c/strong\u003e [0.05\u0026ndash;0.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0\u003c/strong\u003e [0.0-0.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.15\u003c/strong\u003e [0.0-0.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.14\u003c/strong\u003e [0-0.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0027*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAToM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6 [0.5\u0026ndash;0.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45 [0.2\u0026ndash;0.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4 [0.2\u0026ndash;0.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5 [0.1\u0026ndash;0.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0081*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.76\u003c/strong\u003e [0.4\u0026ndash;0.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95 [0.8-1.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.9\u003c/strong\u003e [0.5\u0026ndash;0.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.7\u003c/strong\u003e [0.5\u0026ndash;0.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0038*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTNoT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.43 [0.2\u0026ndash;0.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.15\u003c/strong\u003e [0.0-0.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35 [0.15\u0026ndash;0.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.2\u003c/strong\u003e [0.05\u0026ndash;0.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1308\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eATI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.7\u003c/strong\u003e [0.3\u0026ndash;0.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6 [0.15\u0026ndash;0.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.35 [0.15\u0026ndash;0.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.2\u003c/strong\u003e [0.05\u0026ndash;0.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.3922e-05*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"22\"\u003e\u003cem\u003e*statistically significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/em\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e. \u003cem\u003eabout here\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eAdditionally, we found differences in the TfFTtE and the IB between the assessments in the 1st session and the last, 10th session, substantially significant for all the groups (Table ).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Exergaming performance and functional outcomes\u003c/h2\u003e \u003cp\u003eIn the study with more than hundred patients with MS the groups were almost equally randomized, demonstrating no statistically significant difference in gender, age and EDSS. There were statistically significant differences between the groups in visual-spatial or cognitive capabilities, but no patient's score was bellow the required MMSE value. The visual-spatial test JLO and cognitive and short behavioral test FAB taken before the commencement of the sessions did not show critical or severe impairment, rather average to low average score according to age and education norms (Appollonio et al., 2005) meaning that exergaming should not present a burden. Besides, exergaming has proven effective in people with Parkinson's disease [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]⁠ and a systematic review [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]⁠ also reported on comparable outcomes of exergaming and virtual reality supported balance and gait rehabilitation with conventional training. Additionally we assume that practicing fine motor activities is important for brain excitability [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]⁠. The exergaming of fine motor activities within the performed study contributed to the substantial changes of kinematic parameters and exergame scores in all the groups. The participants evidently got familiar with the exergame and decreased the TNoT consequently achieving better score in the IB. Furthermore, they needed less time for the pick and place task, decreasing the AToM and also the TfFTtE. However, this was not the case for the group 1. Also the statistical test showed significant differences between the groups. The group 1 required more manipulation time (AToM) for each virtual cube. The task with small cubes with bouncing characteristics was confirmed to be the most difficult task. The participants in this group experienced higher HR, but they expressed high level of interest and enjoyment. On contrary the group 4 mastered the task with large and non-bouncing cubes in the first week, finishing each session faster and faster. But their interest/enjoyment rate felt in the second week. The participants of the group 4 reported on low pressure/tension and also low HR was recorded. Most of these findings are consistent with the recent studies [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]⁠, reporting on effects of cognitive load on motor performance in people with MS. The study pointed out a strong correlation of the results with the Montreal Cognitive Assessment - MoCA [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]⁠. The aforementioned study is also in line with our findings that people with MS have a strong ability to improve motor control. We reported on average improvement of the fine motor skills assessed by the BBT in all groups. However, the difference between the groups were not evident and it is difficult to determine which specific game parameter was clinically more relevant. Nevertheless, the improvement of kinematic parameters may provide an insight into the neuromotor mechanism [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]⁠ and is a good supplement to the validated clinical tests.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Suggested exergaming parameters for higher motivation\u003c/h2\u003e \u003cp\u003eImprovement of fine motor skills demonstrated by kinematic assessment may present a valuable information for researchers, but clinicians value the clinical trials with validated test more. Kinematic analysis can highlight the clinical changes in a different perspective, may reveal differences over the treatment that the clinical instrument often neglect due to sensibility [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]⁠. In the study the substantial changes (Cohen's U3) in the intrinsic motivation inventory (IMI) can be explained by the kinematic and game score analysis, particularly in interest/enjoyment and pressure/tension categories. The clinical test showed changes equally for all groups, but the IMI reported on drop of motivation and tension in all groups except group 1. The participant of group 1 handled small and bouncy virtual cubes, difficult to grasp or pinch and often fall out of the hand. The members of the groups 4 and 3 did not have such problem, the later only had to confront the bounciness of the virtual cubes. However, also the bounciness could not be neglected. We found the non-bounciness in group 2 less challenging (interest/enjoyment), but handling small virtual objects and keeping the pressure/tension and the HR high. According to our findings we may rank the difficulty level from easiest (group 4) to the most difficult (group 1). Such exergame parameters can present an important option to control the participants engagement and keep the participants motivated. We have already demonstrated promising results with intrinsic motivation inventory as a key motivation factor for participants [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]⁠. Therefore identification of optimal game parameters would be important to achieve middle term motivation for telerehabilitation and exercises at home.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Limitations of the study and future work\u003c/h2\u003e \u003cp\u003eThe LMC has been validated with golden standard optical measurement systems [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and provide clinically acceptable and meaningful outcomes [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]⁠ thus our kinematic outcomes can be considered reliable. However, we have noticed an occasional unexpected turning of the virtual hand, an unpleasant event making the pick and place task significantly longer. If such an event occurred at least twice in a single session, we would restart and repeat the session. In a case of muscle weakness we may use a passive or active dynamic arm support [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]⁠.\u003c/p\u003e \u003cp\u003eDespite the large number of participants they were randomized into four groups leaving some space for a more extensive study. In the future we may recruit additional participants and provide solid conclusion on the correct choice of virtual object size and behavior for specific neuromuscular disease or disorder.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eWe have demonstrated that the size and behavior of virtual objects have significant impact on functional exercises and motivation of persons with MS. The difficulty level of the task may help the patient to stay focused on the exergame, increase the effort, but consequently also the tension. Particularly the later can result in a higher heart rate. On contrary the easy task has become boring in less than a week. Both middle level options have proven as good. These findings may provide insight into kinematic strategies when using exergaming in occupational and physiotherapy. Additionally, the developers may appreciate such information when designing the complex task for comprehensive and long-term use of such applications in rehabilitation medicine, in particular telerehabilitation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe study (Approval Number: URIS202001) was approved by ethics committee of University Rehabilitation Institute, Republic of Slovenia and all participants provided an informed written consent. The procedure was in accordance with the principles of the Declaration of Helsinki on biomedical research on human beings, the provisions of Council of Europe Convention on the Protection of Human Rights and Dignity of the Human Being with regard to the Application of Biology and Medicine (Oviedo Convention) and the principles of Slovenian Code of medical ethics. The authors confirm that all ongoing and related trials for this drug/intervention are registered (ClinicalTrials.gov Identifier: NCT04266444,\u0026nbsp;12/02/2020, https://clinicaltrials.gov/ct2/show/NCT04266444).\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eAll authors, project group members and participant agreed on publication. Participant provided a written consent for the publication of photographs.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and material\u003c/h2\u003e\n\u003cp\u003eAnonymized\u0026nbsp;data generated or analyzed during this study are available on request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eSlovenian Research Agency (research core funding No. P2-0228).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHealth Insurance Institute of Slovenia.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThe authors would like to thank Klemen Grabljevec, MD, MSc for medical advices, Dejana Zajc, OT, Marta Vidmar, OT, Polonca Rogelj OT, Katja Perme Su\u0026scaron;nik, OT, Gabriela Če\u0026scaron;arek Vučko, OT for assistance with patients and the psychologists Tara Klun, Marjana Kranj Dobre and dr. Ur\u0026scaron;a Čižman \u0026Scaron;taba for providing psychological outcomes. The authors also acknowledge the financial support from the Slovenian Research Agency (research core funding No. P2-0228) and the Health Insurance Institute of Slovenia.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHinrichs J, Finlayson M. - An Overview of Multiple Sclerosis Rehabilitation. Mult Scler Rehabil [Internet]. CRC Press; 2012 [cited 2022 May 27];66\u0026ndash;91. Available from: https://www.taylorfrancis.com/chapters/edit/10.1201/b12666-9/overview-multiple-sclerosis-rehabilitation-jutta-hinrichs-marcia-finlayson\u003c/li\u003e\n\u003cli\u003eCameron M, Finlayson M, Kesselring J. - Multiple Sclerosis Basics. Mult Scler Rehabil [Internet]. CRC Press; 2012 [cited 2022 May 27];32\u0026ndash;57. Available from: https://www.taylorfrancis.com/chapters/edit/10.1201/b12666-7/multiple-sclerosis-basics-michelle-cameron-marcia-finlayson-j\u0026uuml;rg-kesselring\u003c/li\u003e\n\u003cli\u003eHenze T. Recommendations on Rehabilitation Services for Persons with Multiple Sclerosis in Europe endorsed by RIMS, Rehabilitation in Multiple Sclerosis European Multiple Sclerosis Platform (EMSP). Eur Mult Scler Platf. 2012; \u003c/li\u003e\n\u003cli\u003eKurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology [Internet]. Neurology; 1983 [cited 2022 Mar 17];33:1444\u0026ndash;52. Available from: https://pubmed.ncbi.nlm.nih.gov/6685237/\u003c/li\u003e\n\u003cli\u003eKister I, Chamot E, Salter AR, Cutter GR, Bacon TE, Herbert J. Disability in multiple sclerosis: a reference for patients and clinicians. Neurology [Internet]. Neurology; 2013 [cited 2022 Apr 19];80:1018\u0026ndash;24. Available from: https://pubmed.ncbi.nlm.nih.gov/23427319/\u003c/li\u003e\n\u003cli\u003eBertoni R, Lamers I, Chen CC, Feys P, Cattaneo D. Unilateral and bilateral upper limb dysfunction at body functions, activity and participation levels in people with multiple sclerosis. Mult Scler [Internet]. Mult Scler; 2015 [cited 2022 Apr 19];21:1566\u0026ndash;74. Available from: https://pubmed.ncbi.nlm.nih.gov/25662346/\u003c/li\u003e\n\u003cli\u003eSimmons RD. Life issues in multiple sclerosis. Nat Rev Neurol [Internet]. Nat Rev Neurol; 2010 [cited 2022 Apr 19];6:603\u0026ndash;10. Available from: https://pubmed.ncbi.nlm.nih.gov/20856267/\u003c/li\u003e\n\u003cli\u003eGoverover Y, Genova HM, DeLuca J, Chiaravalloti ND. Impact of multiple sclerosis on daily life. Chang Brain Impact Dly Life [Internet]. Springer New York; 2016 [cited 2022 Apr 19];145\u0026ndash;65. Available from: /record/2016-62114-007\u003c/li\u003e\n\u003cli\u003eMassetti T, Trevizan I, Arab C, Favero F, Ribeiro-Papa D, de Mello Monteiro C. Virtual reality in multiple sclerosis - A systematic review. Mult Scler Relat Disord [Internet]. Mult Scler Relat Disord; 2016 [cited 2021 Jul 8];8:107\u0026ndash;12. Available from: https://pubmed.ncbi.nlm.nih.gov/27456884/\u003c/li\u003e\n\u003cli\u003eCikajlo I, Peterlin Potisk K. Advantages of using 3D virtual reality based training in persons with Parkinson\u0026rsquo;s disease: A parallel study. J Neuroeng Rehabil [Internet]. BioMed Central Ltd.; 2019 [cited 2019 Dec 10];16:119. Available from: https://pubmed.ncbi.nlm.nih.gov/31623622/\u003c/li\u003e\n\u003cli\u003eWebster A, Poyade M, Rooney S, Paul L. Upper limb rehabilitation interventions using virtual reality for people with multiple sclerosis: A systematic review [Internet]. Mult. Scler. Relat. Disord. Mult Scler Relat Disord; 2021 [cited 2021 Jul 8]. Available from: https://pubmed.ncbi.nlm.nih.gov/33212400/\u003c/li\u003e\n\u003cli\u003eGuna J, Jakus G, Pogačnik M, Tomažič S, Sodnik J. An Analysis of the Precision and Reliability of the Leap Motion Sensor and Its Suitability for Static and Dynamic Tracking. Sensors [Internet]. Multidisciplinary Digital Publishing Institute; 2014 [cited 2017 Feb 17];14:3702\u0026ndash;20. Available from: http://www.mdpi.com/1424-8220/14/2/3702/\u003c/li\u003e\n\u003cli\u003eMcAuley E, Duncan T, Tammen V V. Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: a confirmatory factor analysis. Res Q Exerc Sport. 1989;60:48\u0026ndash;58. \u003c/li\u003e\n\u003cli\u003eMathiowetz V, Volland G, Kashman N, Weber K. Adult norms for the Box and Block test of manual dexterity. Am J Occup Ther. 1985;39:386\u0026ndash;91. \u003c/li\u003e\n\u003cli\u003eDelis DC, Kaplan E, Kramer JH. Delis-Kaplan Executive Function System: Examiner\u0026rsquo;s manual. San Antonio, TX: The Psychological Corporation; 2001. \u003c/li\u003e\n\u003cli\u003eBenton A, Varney N, Hamsher K. Visuospatial judgment. A clinical test. Arch Neurol [Internet]. Arch Neurol; 1978 [cited 2021 Jul 8];35:364\u0026ndash;7. Available from: https://pubmed.ncbi.nlm.nih.gov/655909/\u003c/li\u003e\n\u003cli\u003eMoore B, Denckla M. Neurofibromatosis. In: Yeates KO, Ris MD, editors. Pediatr Neuropsychol Res Theory, Pract. New York, New York, USA: Guilford Press; 1999. p. 149\u0026ndash;70. \u003c/li\u003e\n\u003cli\u003eDubois B, Slachevsky A, Litvan I, Pillon B. The FAB: a Frontal Assessment Battery at bedside. Neurology [Internet]. Neurology; 2000 [cited 2021 Jul 8];55:1621\u0026ndash;6. Available from: https://pubmed.ncbi.nlm.nih.gov/11113214/\u003c/li\u003e\n\u003cli\u003eAppollonio I, Leone M, Isella V, Piamarta F, Consoli T, Villa ML, et al. The frontal assessment battery (FAB): Normative values in an Italian population sample. Neurol Sci. 2005;26:108\u0026ndash;16. \u003c/li\u003e\n\u003cli\u003eBrown RG, Lacomblez L, Landwehrmeyer BG, Bak T, Uttner I, Dubois B, et al. Cognitive impairment in patients with multiple system atrophy and progressive supranuclear palsy. Brain [Internet]. Oxford Academic; 2010 [cited 2022 Apr 25];133:2382\u0026ndash;93. Available from: https://academic.oup.com/brain/article/133/8/2382/388829\u003c/li\u003e\n\u003cli\u003eColombo R, Pisano F, Mazzone A, Delconte C, Micera S, Carrozza MC, et al. Design strategies to improve patient motivation during robot-aided rehabilitation. J Neuroeng Rehabil. 2007;4. \u003c/li\u003e\n\u003cli\u003eMcAuley E, Duncan T, Tammen V V. Psychometric Properties of the Intrinsic Motivation Inventory in a Competitive Sport Setting: A Confirmatory Factor Analysis. Res Q Exerc Sport [Internet]. 1989 [cited 2019 Feb 13];60:48\u0026ndash;58. Available from: http://www.ncbi.nlm.nih.gov/pubmed/2489825\u003c/li\u003e\n\u003cli\u003eCikajlo I, Pogačnik M. Movement analysis of pick-and-place virtual reality exergaming in patients with Parkinson\u0026rsquo;s disease. Technol Health Care [Internet]. NLM (Medline); 2020 [cited 2020 Aug 25];28:391\u0026ndash;402. Available from: https://pubmed.ncbi.nlm.nih.gov/32200361/\u003c/li\u003e\n\u003cli\u003eSkillings JH, Mack GA. On the Use of a Friedman-Type Statistic in Balanced and Unbalanced Block Designs. Technometrics [Internet]. 1981 [cited 2019 Feb 14];23:171\u0026ndash;7. Available from: http://www.tandfonline.com/doi/abs/10.1080/00401706.1981.10486261\u003c/li\u003e\n\u003cli\u003eCohen J. Statistical power analysis for the behavioral sciences. Academic Press; 1977. \u003c/li\u003e\n\u003cli\u003eHentschke H, St\u0026uuml;ttgen MC. Computation of measures of effect size for neuroscience data sets. Eur J Neurosci [Internet]. 2011 [cited 2019 Apr 2];34:1887\u0026ndash;94. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22082031\u003c/li\u003e\n\u003cli\u003eYuan RY, Chen SC, Peng CW, Lin YN, Chang YT, Lai CH. Effects of interactive video-game-based exercise on balance in older adults with mild-to-moderate Parkinson\u0026rsquo;s disease. J Neuroeng Rehabil. BioMed Central; 2020;17. \u003c/li\u003e\n\u003cli\u003eCasuso-Holgado MJ, Mart\u0026iacute;n-Valero R, Carazo AF, Medrano-S\u0026aacute;nchez EM, Cort\u0026eacute;s-Vega MD, Montero-Bancalero FJ. Effectiveness of virtual reality training for balance and gait rehabilitation in people with multiple sclerosis: a systematic review and meta-analysis. Clin Rehabil. SAGE Publications Ltd; 2018;32:1220\u0026ndash;34. \u003c/li\u003e\n\u003cli\u003eLulic T, El-Sayes J, Fassett HJ, Nelson AJ. Physical activity levels determine exercise-induced changes in brain excitability. Antal A, editor. PLoS One [Internet]. Public Library of Science; 2017 [cited 2019 Feb 4];12:e0173672. Available from: https://dx.plos.org/10.1371/journal.pone.0173672\u003c/li\u003e\n\u003cli\u003eAl-Sharman A, Khalil H, El-Salem K, Alghwiri AA, Khazaaleh S, Khraim M. Motor performance improvement through virtual reality task is related to fatigue and cognition in people with multiple sclerosis. Physiother Res Int [Internet]. Physiother Res Int; 2019 [cited 2021 Jul 8];24. Available from: https://pubmed.ncbi.nlm.nih.gov/31120581/\u003c/li\u003e\n\u003cli\u003eDagenais E, Rouleau I, Demers M, Jobin C, Roger E, Chamelian L, et al. Value of the MoCA test as a screening instrument in multiple sclerosis. Can J Neurol Sci. 2013;40:410\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003eMaier M, Ballester BR, Verschure PFMJ. Principles of Neurorehabilitation After Stroke Based on Motor Learning and Brain Plasticity Mechanisms [Internet]. Front. Syst. Neurosci. Frontiers Media S.A.; 2019 [cited 2021 Jan 6]. p. 74. Available from: www.frontiersin.org\u003c/li\u003e\n\u003cli\u003eJohansson GM, Grip H, Levin MF, H\u0026auml;ger CK. The added value of kinematic evaluation of the timed finger-to-nose test in persons post-stroke. J Neuroeng Rehabil [Internet]. BioMed Central Ltd.; 2017 [cited 2022 May 12];14:1\u0026ndash;12. Available from: https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-017-0220-7\u003c/li\u003e\n\u003cli\u003eGorsic M, Cikajlo I, Novak D, Gor\u0026scaron;ič M, Cikajlo I, Novak D. Competitive and cooperative arm rehabilitation games played by a patient and unimpaired person: effects on motivation and exercise intensity. J Neuroeng Rehabil [Internet]. 2017 [cited 2018 Oct 1];14:23. Available from: http://www.ncbi.nlm.nih.gov/pubmed/28330504\u003c/li\u003e\n\u003cli\u003eNiechwiej-Szwedo E, Gonzalez D, Nouredanesh M, Tung J. Evaluation of the Leap Motion Controller during the performance of visually-guided upper limb movements. PLoS One [Internet]. Public Library of Science; 2018 [cited 2022 May 10];13:e0193639. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0193639\u003c/li\u003e\n\u003cli\u003eSmeragliuolo AH, Hill NJ, Disla L, Putrino D. Validation of the Leap Motion Controller using markered motion capture technology. J Biomech [Internet]. J Biomech; 2016 [cited 2022 May 10];49:1742\u0026ndash;50. Available from: https://pubmed.ncbi.nlm.nih.gov/27102160/\u003c/li\u003e\n\u003cli\u003eVan Der Heide LA, Van Ninhuijs B, Bergsma A, Gelderblom GJ, Van Der Pijl DJ, De Witte LP. An overview and categorization of dynamic arm supports for people with decreased arm function [Internet]. Prosthet. Orthot. Int. SAGE Publications Ltd; 2014 [cited 2020 Sep 4]. p. 287\u0026ndash;302. Available from: https://research.tue.nl/en/publications/an-overview-and-categorization-of-dynamic-arm-supports-for-people\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"multiple sclerosis, rehabilitation, virtual reality, exergaming, perception, upper extremities, intrinsic motivation inventory","lastPublishedDoi":"10.21203/rs.3.rs-1707133/v2","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1707133/v2","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: The consequences of multiple sclerosis are problems related to movement of extremities, coordination and vision. Heretofore frequent treatment with additional medications can change the course of the disease. Motor relearning of small range movements are important to support daily living activities.\u0026nbsp;We have designed a virtual environment for pick and place task. The user hand and finger movements were tracked with a small infrared camera. The primary objective of the study was to examine the influence of size and behavior of virtual cubes on motor control, motivation and functional performance.\u0026nbsp;The secondary objective was to examine the changes of heart rate and intensity of the task due to the different size and behavior of the virtual objects. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: In the randomized study 84/107 eligible inpatients with multiple sclerosis participated. They were randomized into 4 groups by computer random function; group 1 - small and bouncing, group 2 - small and non-bouncing, group 3 - big and bouncing and group 4 - big and non-bouncing virtual cubes. Each participant took 50 sessions, each up to 2 min in approximately 14 days. Before commencement of the study the participants took visual-spatial and cognitive tests. The participants’ subjective experiences was assessed daily with Intrinsic Motivation Inventory. Box and Blocks Test was carried out before and after the study.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: In the study the group 4 was the most successful (inserted cubes \u0026gt; 9) and the fastest (63.4 SD 25.8 s).\u0026nbsp;The group 1 was the slowest (88.9 SD 28.2 s), but with high\u0026nbsp;interest/enjoyment rate and pressure/tension at high heart rate. There were substantial differences in intrinsic motivation between the 1st and the last session within the groups (Cohen's U3\u0026nbsp;\u0026lt; 0.3 or \u0026gt; 0.8). Kinematic analysis showed differences between the groups (average manipulation time p = 0.008, inserted cubes p = 0.004).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: The size and behavior of virtual objects may be crucial for the motivation of participants with equal visual-spatial and cognitive capabilities while maintaining effort and keep trying to improve their performance. Furthermore, the clinical outcomes can confirm the effectiveness of the approach.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTrial registration\u003c/strong\u003e: The small scale randomized pilot trial has been registered at ClinicalTrials.gov Identifier: NCT04266444, 12/02/2020, https://clinicaltrials.gov/ct2/show/NCT04266444\u003c/p\u003e","manuscriptTitle":"The Size and Behavior of Virtual Objects have influence on Functional Exercise and Motivation of Persons with Multiple Sclerosis: a randomized study","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2022-07-08 15:59:27","doi":"10.21203/rs.3.rs-1707133/v2","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2022-10-04T10:44:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-10-04T07:13:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4eb679ac-afa7-41e9-98d1-3d9d9c3fe360","date":"2022-09-19T09:58:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2022-09-13T15:05:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"40a53e52-9b27-426e-bd74-21e98f352491","date":"2022-09-09T14:30:24+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2022-08-02T10:45:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2022-08-02T10:42:13+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2022-06-25T08:04:09+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2022-06-25T07:36:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2022-06-09T07:53:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"82b05a6a-030a-4164-a56b-94d007176aa5","owner":[],"postedDate":"July 8th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2022-11-09T07:59:30+00:00","versionOfRecord":[],"versionCreatedAt":"2022-07-08 15:59:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v2","identity":"rs-1707133","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1707133","identity":"rs-1707133","version":["v2"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}