Examining the effect of verbal feedback vs. real-time software feedback on kinetic and kinematic metrics of the Nordic hamstring exercise

Examining the effect of verbal feedback vs. real-time software feedback on kinetic and kinematic metrics of the Nordic hamstring exercise | 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 Research Article Examining the effect of verbal feedback vs. real-time software feedback on kinetic and kinematic metrics of the Nordic hamstring exercise Emma SCONCE, Ben HELLER, Tom MADEN-WILKINSON, Nick HAMILTON This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4158884/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Dec, 2024 Read the published version in Sport Sciences for Health → Version 1 posted 7 You are reading this latest preprint version Abstract Purpose A wealth of research exists for the Nordic hamstring exercise, and several devices provide real-time feedback on torque profiling. However, none currently offer feedback on technique execution. This study investigated the effect of verbal and software feedback on Nordic exercise kinetic and kinematic metrics. Methods 24 recreational participants completed 3 bilateral repetitions per feedback condition on a hamstring testing device. Hamstring strain injury risk metrics (peak torque, break-torque angle, bilateral limb percentage difference) and exercise technique metrics (relative trunk-to-thigh angle, angular velocity of the knee) were recorded for analysis. Results Feedback type significantly affected eccentric knee flexor peak torque, by a mean decrease of 7.1 Nm when performed with software feedback (Cohen’s d = 0.238, p < 0.01). Altering feedback had no significant effect on bilateral limb difference percentage (Cohen’s d = 0.068, p = 0.578) or break-torque angle (Cohen’s d = 0.159, p = 0.115). Software feedback significantly decreased the mean of both the relative-trunk-to-thigh angle at peak torque by 5.7° (Cohen’s d = 0.514, p < 0.01) and the angular velocity of the knee at peak torque by 8.7 deg·s-1. Conclusions An integrated software feedback system significantly improves acute Nordic exercise technique, benefitting individuals initially exhibiting poorer technique the most. Nordic hamstring exercise software feedback technique Figures Figure 1 Figure 2 Figure 3 Introduction A conventional Nordic hamstring exercise (NHE) is performed with an athlete assuming a kneeling start position, with the hips fully extended and the torso held upright and rigid [ 1 ]. From this position, athletes perform a controlled forward rotation action about the knee. In the majority of studies, athletes are informed to gradually lean forward at the slowest possible speed, maximally resisting the forward-falling movement with both legs, whilst holding the hips fixed in line with the knee and shoulder joints throughout the range of movement, keeping a neutral position throughout [ 1 – 4 ]. Factors affecting the quality of an NHE trial include having a distinct peak torque, maintaining a neutral hip flexion angle and performing a controlled descent speed [ 5 , 6 ]. Previous work by Sconce et al. [ 7 ] reported poor overall NHE exercise technique and high intrasubject variability for both relative trunk-to-thigh angle at peak-torque (RTA) ( range = 0.4–44.7°), and angular velocity of the knee at peak-torque (AVK) ( range = 3.6–93.4deg·s − 1 ) in 127 NHE trials (n = 18). Poor NHE technique can be problematic as excessive hip flexion produces larger NHE torque values at the same knee angle compared to a neutral hip position, which can lead to unreliable results between groups. This is due to the increased lever arm of the centre of mass about the knee joint axis influencing the torque-length relationship, increasing the resultant torque [ 8 , 9 ]. Therefore, the hip flexion angle should be controlled to allow accurate comparison between athletes [ 10 ]. Increasing hip flexion lengthens hamstring musculature, as observed in razor curl training [ 11 ] however this exercise does not allow for a break-point, which is required for assessing the length of the muscle at which failure occurs. Conversely, hip angular acceleration (‘breaking’ at the hip) reduces the knee flexor torque required to achieve a specific knee angle. In the current literature, NHE descent speed has generally been assessed visually and enforced through verbal instruction; using a very slow approach throughout the active range of motion (ROM) or descending to an average cadence of 30deg·s − 1 using a metronome [ 12 – 15 ]. AVK influences resultant torque, due to a shift of the torque-velocity relationship and also results in less time for the knee flexors to decelerate and control the forward action. This reduces time-under tension (TUT) which is important in NHE training for hypertrophy, specific muscle fibre recruitment, muscular endurance, metabolic stress, and motor unit activation [ 16 ]. A controlled descent ensuring a maximal break-point is important for determining accurate muscle torque-length capabilities of the knee flexors, such as break-torque angle (BTA). The controlled descent focuses directly on optimising recruitment of the hamstring muscle complex for preventing strain injury risk, rather than the accessory muscles of the gluteus maximus, gastrocnemius, erector spinae, and adductors [ 7 ]. Furthermore, as suggested by Alt and Schmidt [ 5 ] poor NHE execution may impede or even prevent adaptations at long hamstring muscle lengths occurring at extended knee angles. Few studies have considered exercise technique whilst performing the NHE. Alt and Schmidt [ 5 ] have proposed clear NHE training execution quality criteria (ANHEQ), recommending that NHEs should be executed with a constant knee extension velocity of 15deg·s − 1 across the largest possible knee ROM (in a supramaximal unassisted NHE this would be up until ‘break-point’) with a suggested time under tension of ~ 6.5 seconds per repetition. Moreover, they propose the eccentric phase of the NHE should be performed with minimal hip flexion, keeping the hands situated close to the shoulders, which is typical in the majority of the research [ 2 , 14 , 17 – 19 ]. This provides useful recommendation targets for NHE-assisted training; however, as found by Sconce et al. [ 20 ] is difficult to implement for supramaximal NHE testing. We propose that integrating a software feedback system for testing can standardise NHE trials [ 21 ]. Moreover, controlling RTA and AVK (up until break-point) will provide consistent data, ensuring injury risk metrics (eccentric knee flexor peak torque and BTA) can be reliably reproduced between groups of athletes. It is well recognised that performance can be improved by augmented feedback (feedback from an external source provided as knowledge of performance or result) [ 22 , 23 ]. This type of feedback is often used during resistance training to enhance acute physical performance and has shown promise as a method for improving chronic physical adaptation [ 24 – 27 ]. However, in a systematic review and meta-analysis by Weakley et al. [ 28 ] it is reported that the magnitude of the response and the optimal method with which feedback is provided is inconsistent between studies. The application of visual and/or verbal augmented feedback, and more recently feedback through visual and/or audible applications (apps) can help increase the rate of learning which may reduce some injury risk factors [ 21 ]. Feedback has been shown to significantly increase eccentric knee flexion force output when traditionally measured on isokinetic dynamometry [ 29 , 30 ]. Most current hamstring testing and training devices offer kinetic feedback in the form of live graphical representation of force or torque traces using integrated dashboard software [ 31 – 33 ], with results stored on a centralised cloud data storage and analytics platform. Results can be seen in real-time with immediate feedback for metrics such as bilateral hamstring strength, between-limb strength imbalances, and average strength across repetitions [ 21 , 31 , 34 – 36 ]. Most studies have only used verbal researcher encouragement or a metronome to control hip flexion and descent speed, rather than specific computer feedback. Few studies have used visual NHE feedback [ 13 , 21 , 37 , 38 ], and very limited studies [ 21 , 27 ] have studied the effect of feedback on NHE metrics, and none to our knowledge examining the effect of both kinetic and kinematic feedback on NHE exercise technique metrics. The study by Chalker et al. [ 21 ] examined the effect real-time visual dashboard software feedback had on NHE force outputs and kinetic metrics such as eccentric knee flexor strength and bilateral force production between limb asymmetries [ 21 ]. They reported that when feedback was provided on a hamstring testing device there was a significant increase in mean peak force production (mean diff. 21.7N) and no significant difference between limb asymmetry for feedback or no feedback (mean diff 5.7%). The increase in force production with feedback was attributed to an increased weaker limb force contribution compared to the stronger limb (mean diff 15.0N). However, there is little other published literature available regarding the influence of software feedback on NHE kinetic or kinematic metrics. Alt and Schmidt [ 5 ] state that for NHE intervention studies, standard training procedures should specify a constant target movement speed to obtain reliable results, and it is recommended to use a monitor to provide angle-time information in real-time to participants. This study aims to develop a novel, robust visual feedback NHE execution technique system and examine its effect on injury risk and technique metrics. The objective is to integrate a software system within the existing HA L HAM° device [ 7 ] to monitor hip position and knee extension speed. It is hypothesised that software feedback will improve exercise technique. Methods Participants Twenty-four recreationally active participants (n = 24) of varying NHE training experience, gender, and age were recruited to participate in this study (Mean ± SD age 29 + 11 years, height 177 ± 8.3cm, and body mass 78.6 ± 14.1kg). With exercise technique being the feedback focus, and this being explanatory research, a diverse representation of participants was chosen to offer a more holistic understanding of technique challenges and the impact of feedback. All participants completed an initial questionnaire, used to gather data medical and injury data. Exclusion criteria included a lower extremity injury in the previous 6 months, or a history of recurrent low-back, hip, thigh, or knee injuries. Furthermore, all participants self-declared as being physically fit and free from any health or medical conditions that would contraindicate or impede them from performing maximal NHE testing. After having all procedures explained to them, participants provided written informed consent to participate in the spirit of the Helsinki Declaration, before testing commenced. Ethical approval for the study was approved by the Universities Ethics Committee. Experimental protocol/Design The HA L HAM° NHE custom device developed by Sconce et al. [ 7 , 20 ] was used to collect the data. Strain gauge load cells (DYMH-103 Micro Miniature Load Cell) measured individual right and left limb forces, and the software displayed these and combined limb total forces as force-time traces in line graph format. Torque was calculated for each NHE trial from the force measured by the load cells and the distance measured from the set pivot point (0.661m). Participants’ NHE starting position was determined by lining up the lateral femoral epicondyle of the femur with the pivot point before commencement [ 7 ]. An IMU (MOT1101_0, Phidgets Inc, Calgary, Canada) was positioned on a custom-made plastic carrier with pointed ends to help align the sensor laterally on the upper leg at an equal distance away from the greater trochanter and lateral femoral epicondyle. The IMU trunk sensor was also positioned laterally at an equal distance from the greater trochanter to the shoulder bursa. For the verbal feedback (VF) condition the researcher instructed participants to gradually lean forward at the slowest possible speed maintaining a neutral trunk alignment with the hips fixed in line with the knee and shoulder joints [ 2 ], whilst holding the hands in line with the shoulders, palms facing forward. Avoidance of hyperextension was advised. Participants were asked to perform the Nordic action until they could no longer withstand the torque around their knee flexors, using their hands to buffer the fall onto a fixed platform [ 1 , 4 ]. The software feedback (SF) was a custom-made visual system using an on-screen mannequin representation of a person and a pre-determined reference line to provide visual cues for the user ( Fig. 1 ). The IMU sensors tracked the user’s knee and hip flexion angles in real time and used these to animate the mannequin. The superimposed dynamic reference line extended from the mannequin’s lateral epicondyle through the greater trochanter, to the shoulder bursa. Speed was set at 20deg·s − 1 which was determined from previous work [ 7 , 20 ] and is comparative to the NHE velocity used in the literature [ 38 , 39 ]. Hip flexion was set at 0° to encourage a neutral position throughout the range of motion. As the user performed the NHE action, they were prompted to match the movement of the reference line with the virtual representation on-screen. A monitor was positioned on a stand on the floor, at the base of the HA L HAM° platform to suit the eye-line position. The grey reference line warned the user of deviation from the set optimal hip angle and speed by turning orange as a warning if within a range of 5° and then red if greater than 5° from the set coordinates ( Fig. 1 ). Raw IMU data was acquired on a personal computer via a Phidget Bridge data acquisition board (Phidgets Inc., Calgary, Canada). The IMU data were converted into angles using a custom-coded program implementing a complementary filter and then exported in .CSV format. Using MATLAB R2020b software (MathWorks, Inc., Natick, MA) the following variables were subsequently calculated using a custom script: Injury risk metrics as proposed in Sconce et al. [ 20 ]: Peak torque ~ NHE bilateral maximum torque value. Break-torque angle (BTA) ~ representing the knee and corresponding thigh angle at the instant that peak torque occurred. Full extension is represented as 180 degrees. Bilateral limb torque difference (BLD) ~ representing the percentage difference between the right and left leg maximum torque values. Exercise technique metrics as proposed in Sconce et al. [ 20 ]: Relative trunk-to-thigh angle (RTA) ~ the angle in the sagittal plane between the thigh and the trunk throughout the NHE ROM, representing hip angle. RTA at peak torque was then determined. Angular velocity of the knee joint (AVK) ~ representing the angular velocity of the knee joint throughout the NHE ROM, filtered using an 11-point average. AVK at peak torque was then determined. Trials Prior to performing the trials participants were instructed to perform an individual warm-up by using a stationary bike or rower for 3–5 minutes and completing dynamic movements such as arm and hip circles, leg swings, heel-to-toe walks, knee hugs, walking lunges, and squats (2 sets of 10 repetitions). A crossover randomised design was used so that all participants received verbal instruction and real-time software feedback on NHE technique over 2 separate sets of 3 maximal repetitions (6 maximal repetitions overall). The rest period between repetitions was long enough to allow the participant to comfortably recover for the next maximal effort and was advised as ~ 6s [ 5 ]. The rest period between feedback types was substantial, at least 15 minutes, allowing for complete recovery. The order of performing the feedback (either VF or SF first) was randomised between participants. Statistical analysis 144 trials from 24 participants (n = 24) were initially considered (72 trials for each feedback condition). Data from the HA L HAM° IMU’s were treated in MATLAB R2020b software (MathWorks, Inc., Natick, MA) and the data was subsequently statistically processed in GraphPad Prism 8.43 (GraphPad Software Inc). Trial exclusion criteria were no clear peak in the force-time trace, an extended flattened period, or no clear torque drop-off period; no trials were rejected. Descriptive statistics for all trials were calculated and reported as mean ± standard deviation (Table 1 ) . Normality of data was confirmed using an appropriate test (Shapiro-Wilk) and a visual check of a Quantile-Quantile plot. The average of each participant’s 3 trials was calculated, and multiple independent t-tests were performed to compare differences in each metric between feedback conditions (VF and SF). Metrics compared were peak eccentric knee flexor torque (Nm), BTA (°), BLA (%), RTA (°) at peak torque, and AVK (deg·s − 1 ) at peak torque. Where appropriate, effect sizes were calculated by Cohen d and interpreted as small (d ≥ 0.2), moderate (d ≥ 0.5), and large (d ≥ 0.8) [ 40 ]. Results Injury risk factor metrics Changes in mean peak torque, BLD, and BTA with feedback type can be seen in Table 1 and Fig. 2 . Feedback type significantly affected eccentric knee flexor peak torque (d = 0.238 ( Small ), p < 0.01) which lowered when the NHE was performed with SF showing a mean decrease of 7.1Nm compared to VF. Altering feedback had no significant effect on BLD (d = 0.068, p = 0.578) or BTA (d = 0.159, p = 0.115). Exercise technique metrics RTA and AVK changes with feedback can be seen in Table 1 and Fig. 3 . RTA significantly decreased with SF (d = 0.514 ( Moderate ), p < 0.01) showing a mean decrease of 5.7° compared to VF. AVK significantly decreased with SF (d = 0.825 ( Large ), p < 0.01) showing a mean decrease of 8.7deg·s − 1 compared to VF. Table 1 Mean ± SD, and range reported for each metric per feedback condition (n = 24) Verbal Feedback Software Feedback Metrics Mean ± SD Range (Min-Max) Mean ± SD Range (Min-Max) Kinetics Peak torque (Nm) 79.7 ± 31.4* a 32.7–148.4 72.6 ± 27.9* a 36.2–142.1 Kinematics BLD (%) 10.8 ± 6.4 2.9–30.6 11.2 ± 6.5 4.2–29.9 BTA (°) 118.8 ± 9.8 102.0–141.3 120.3 ± 9.1 106.5–146.2 RTA (°) at peak-torque 22.1 ± 13.2* b 1.7–57.9 16.4 ± 8.7* b 2.3–34.6 AVK (deg·s -1 ) at peak-torque 24.6 ± 13.5* c 5.8–61.6 15.9 ± 5.9* c 3.5–26.7 Nm Newton-metre, % percentage difference, ° degrees, deg·s − 1 degrees per second BLD Bilateral limb torque difference, BTA Break-torque angle, RTA Relative trunk-to-thigh angle, AVK Angular velocity of the knee * denotes a significant difference between VF and SF (p < 0.01) a denotes a small effect size b denotes medium effect size c denotes large effect size Discussion The findings affirm the hypothesis that SF enhances acute NHE exercise quality, agreeing with the systematic review findings by Weakley et al. [ 28 ]. They reported that resistance training feedback has a positive influence on immediate performance and can improve favourable adaptations over the long term. Both technique metrics significantly improved (Table 1 and Fig. 3 ) however, performance metrics demonstrated either no significant change or a negatively impacted significant effect with SF (Table 1 and Fig. 2 ). BLD percentage and BTA showed no significant change between feedback conditions and peak torque significantly decreased with SF by a mean decrease of 7.1 Nm compared to VF. This is unsurprising, however, as it is known that a controlled NHE action (neutral hip and slower) will left-ward shift the torque-length and torque-velocity relationships [ 41 , 42 ]. Moreover, the SF was intentionally confined to modify NHE hip flexion and speed exclusively, and not injury risk factor metrics. Interestingly the upper ranges dropped significantly (Table 1 and Fig. 3 ) with SF for both RTA (57.9° to 34.6°) and AVK (61.6 deg·s − 1 to 26.7 deg·s − 1 ), which suggests that individuals initially exhibiting poorer exercise technique showed the most improvement, bringing them closer to the normal ranges. The literature shows the impact of different hamstring exercises on muscle architecture and morphology and the implications this can have for injury prevention [ 43 – 45 ]. Notably, both the NHE and hip extension exercises stimulate significant increases in Biceps femoris long head (BFlh) fascicle length, however, the NHE is reported to be more effective in promoting hypertrophy in the BFlh [ 43 ]. Furthermore, a study by Baumgart et al. [ 44 ] reported that parametric and angle-specific flexion and extension torques differ according to hip flexion, velocity, and muscle contraction mode. Hamstring muscles operate differently across different lengths in response to changing exercise stimuli [ 45 ] and studies have suggested that injury is associated with a left-ward shift of peak torque to shorter angle lengths in the hamstrings [ 46 ]. The evaluation of the torque-angle relationship may be a useful tool for predicting hamstring strain injuries and as a return-to-play measure [ 47 ]. Therefore, standardized, controlled technique of exercises that measure torque-angular data is important, as a deviation of form can alter the intended nature of the exercise, impacting the desired adaptations in the knee flexors, whether for training, angle-specific testing, performance optimisation, injury prevention or rehabilitation. Chalker et al. [ 21 ] reported an increase in mean peak force production when using feedback, however it was specific to force-time traces on a screen and not hip and knee angles, or movement velocity. Moreover, if increased torque is a result of suboptimal exercise technique, there is a risk of overestimation which has implications in hamstring training intervention studies where precise quantification of change is important for assessing the effectiveness of the intervention [ 48 ]. Additionally, the production of peak torque within a shorter muscle length range is less useful for targeting the site of hamstring injuries [ 10 , 46 ]. It is, therefore, reasonable to hypothesise that integrating SF into chronic NHE training, using a moving reference line on-screen and supplementing it with the option to visualise torque-time traces and break-point failures as part of a performance/injury-risk software mode would be beneficial. Several advantages of the biofeedback system include immediate user correction, engagement, and better exercise technique. The system reinforces proper NHE form by visually guiding users through the correct range of motion and pace. Real-time feedback helps avoid overextension or rapid movements that could lead to strain. As users receive immediate visual cues, they can make adjustments allowing them to course-correct during the exercise. The visual representation and reference line create an interface experience, encouraging users to maintain focus and adherence, which is a major issue in NHE compliance [ 49 ]. It is suggested that acute feedback is most beneficial when of high frequency (during every rep), and of a visual kinematic nature [ 27 ] which the HA L HAM° SF system offers. Limitations of the study are relatively modest sample numbers, and the absence of a separate pre-testing familiarisation phase as noted in Alt and Schmidt [ 5 ]. Nonetheless, our focus examined changes in metrics with SF rather than preparing athletes for exhaustive performance testing or training. User feedback recommended that the reference line start from a position behind neutral, featuring an initial slightly flexed knee position with a ‘preliminary movement phase’ to allow the user to adjust to the pace before passing through the neutral position. As a result, the test is then initiated in a manner that ensures a controlled and smoother commencement. Another consideration for SF adjustment would be defining an anatomically aligned hip flexion angle reflecting natural physiological curvature of the lumbar spine, within a permissible range of up to 20° as suggested by, Alt and Schmidt [ 5 ]. This modification would expand the cautionary orange range to encompass values up to this threshold and subsequently set the red range beyond it. Alt and Schmidt [ 5 ] recommend NHEs should be executed with a constant knee extension velocity of 15deg·s − 1 across the NHE range of motion, with a 10deg·s − 1 deviation of this being classed as the break-point (failure). Again, setting a cautionary range for AVK of between 15–25 deg·s − 1 should be explored in future work. Implementing a flexible SF system for NHE training where the individual could customise the AVK and RTA threshold, would be advisable. This would support the required muscle adaptations required for personalised hamstring training. For instance, faster eccentric loading velocity could be advantageous for recruiting higher hamstring muscle activation [ 50 ], whereas a slower velocity with controlled hip flexion might be preferable for optimising TUT, without using the accessory muscles to maximise the preferential protective adaptations of hypertrophy and longer BFlh fascicle length required for HSI prevention. Ongoing user familiarisation of the feedback system over the long term would be required to evaluate its effectiveness for this type of purpose. Conclusion The HA L HAM° integrated SF system significantly improves acute NHE technique (RTA and AVK), benefitting individuals initially exhibiting poorer technique the most. A customizable SF system with a performance mode option may be beneficial for NHE chronic intervention training and testing to elicit desired protective muscular adaptations and lower hamstring strain injury risk. Abbreviations AVK Angular velocity of the knee joint BFlh Biceps femoris long head BLD Bilateral limb difference BTA Break-torque angle HSI Hamstring strain injury NHE Nordic hamstring exercise RTA Relative trunk-to-thigh angle SF Software feedback TUT Time-under-tension VF Verbal feedback Declarations Disclosure of interest: The authors report no conflict of interest. Consent to participate: Informed consent was obtained from all individual participants included in the study. Consent to publish: Participants signed informed consent regarding publishing their data. Funding: No funding was received for conducting this study. Ethics Approval: The study was performed in line with the principles of the Declaration of Helsinki. Ethical approval for the study was approved by the Sheffield Hallam University Ethics Committee (Date: 24/03/2021/No ER29609708). Data availability statement: The data that support the findings of this study are available from the corresponding author, [ES], upon reasonable request. Authors' contribution statement : : ES, BH, TMW and NH were responsible for the conception of the study. NH and BH were responsible for the design and implementation of the device hardware and software. ES was involved in the data collection and conducted the analyses. ES drafted the manuscript, which was critically revised by the coauthors. References Petersen J, Thorborg K, Nielsen MB, et al (2011) Preventive effect of eccentric training on acute hamstring injuries in men’s soccer: A cluster-randomized controlled trial. 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Am J Sports Med 43:2663–2670. https://doi.org/10.1177/0363546515599633 Timmins RG, Bourne MN, Shield AJ, et al (2016) Short biceps femoris fascicles and eccentric knee flexor weakness increase the risk of hamstring injury in elite football (soccer): A prospective cohort study. Br J Sports Med 50:1524–1535. https://doi.org/10.1136/bjsports-2015-095362 Lodge C, Tobin D, Rourke BO, Thorborg K (2020) Reliability and validity of a new eccentric hamstring strength measurement device. Arch Rehabil Res Clin Transl 2:1–6. https://doi.org/10.1016/j.arrct.2019.100034 Timmins RG, Shield AJ, Williams MD, Opar DA (2016) Is there evidence to support the use of the angle of peak torque as a marker of hamstring injury and re-injury risk? Sport Med 46:7–13. https://doi.org/10.1007/s40279-015-0378-8 Buchheit M, Cholley Y, Nagel M, Poulos N (2016) The effect of body mass on eccentric knee-flexor strength assessed with an instrumented Nordic hamstring device (Nordbord) in football players. Int J Sports Physiol Perform 11:721–726. https://doi.org/10.1123/ijspp.2015-0513 Opar DA, Piatkowski T, Williams MD, Shield AJ (2013) A novel device using the Nordic hamstring exercise to assess eccentric knee flexor strength: A reliability and retrospective injury study. J Orthop Sport Phys Ther 43:636–640. https://doi.org/10.2519/jospt.2013.4837 Alt T, Nodler YT, Severin J, et al (2018) Velocity specific and time-dependent adaptations following a standardized Nordic hamstring exercise training. Scand J Med Sci Sports 28:65–76. https://doi.org/10.1111/sms.12868 Alt T, Knicker AJ, Nodler YT, Strüder HK (2023) What are we aiming for in eccentric hamstring training: angle-specific control or supramaximal stimulus? J Sport Rehabil 32:782–289 Crawford SK, Hickey J, Vlisides J, et al (2023) The effects of hip vs. knee dominant hamstring exercise on biceps femoris morphology, strength, and sprint performance: a randomized intervention trial protocol. BMC Sports Sci Med Rehabil 15:1–12 Cohen J (2013) Statistical power analysis for the behavioural sciences. Routledge: Taylor & Francis Pollard CW, Bourne MN, Timmins RG, Opar DA (2019) Razor hamstring curl and Nordic hamstring exercise architectural adaptations: Impact of exercise selection and intensity. Scand J Med Sci Sports 29:706–715. https://doi.org/10.1111/sms.13381 Augustsson J, Alt T, Andersson H (2023) Speed Matters in Nordic Hamstring Exercise: Higher Peak Knee Flexor Force during Fast Stretch-Shortening Variant Compared to Standard Slow Eccentric Execution in Elite Athletes. Sports 11:1–12. https://doi.org/10.3390/sports11070130 Bourne M, Duhig S, Timmins R, et al (2017) Impact of the Nordic hamstring and hip extension exercises on hamstring architecture and morphology: Implications for injury prevention. Br J Sports Med 51:469–477. https://doi.org/10.1136/bjsports-2016-096130 Baumgart C, Kurz E, Freiwald J, Hoppe MW (2021) Effects of hip flexion on knee extension and flexion isokinetic angle-specific torques and HQ-ratios. Sport Med - Open 7:1–10. https://doi.org/10.1186/s40798-021-00330-w Kellis E, Blazevich AJ (2022) Hamstrings force-length relationships and their implications for angle-specific joint torques: a narrative review. BMC Sports Sci Med Rehabil 14:1–34. https://doi.org/10.1186/s13102-022-00555-6 Brockett CL, Morgan DL, Proske U (2004) Predicting hamstring injury in elite athletes. Med Sci Sports Exerc 36:379–387. https://doi.org/10.1249/01.MSS.0000117165.75832.05 Brughelli M, Cronin J (2007) Altering the length-tension relationship with eccentric exercise: Implications for performance and injury. Sport Med 37:807–826. https://doi.org/10.2165/00007256-200737090-00004 Amundsen R, Møller M, Bahr R (2023) Performing Nordic hamstring strength testing with additional weight affects the maximal eccentric force measured: do not compare apples to oranges. BMJ Open Sport Exerc Med 9:1–6. https://doi.org/10.1136/bmjsem-2023-001699 Horst N Van Der, Hoef S Van De, Otterloo P Van, Klein M (2021) Effective but not adhered to: how can we improve adherence to evidence-based hamstring injury prevention in amateur football? 31:42–48 Zehr EP, Sale DG (1994) Ballistic movement: Muscle activation and neuromuscular adaptation. Can J Appl Physiol 19:363–378. https://doi.org/10.1139/h94-030 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 01 Dec, 2024 Read the published version in Sport Sciences for Health → Version 1 posted Editorial decision: Revision requested 29 Aug, 2024 Reviews received at journal 24 Aug, 2024 Reviewers agreed at journal 22 Aug, 2024 Reviewers invited by journal 02 Aug, 2024 Submission checks completed at journal 24 Mar, 2024 Editor assigned by journal 24 Mar, 2024 First submitted to journal 24 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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-4158884","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":283364020,"identity":"9f0becc3-3ddf-4bf4-a44f-191c3669d1cd","order_by":0,"name":"Emma SCONCE","email":"data:image/png;base64,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","orcid":"","institution":"Sheffield Hallam University","correspondingAuthor":true,"prefix":"","firstName":"Emma","middleName":"","lastName":"SCONCE","suffix":""},{"id":283364021,"identity":"27ecd065-fa81-4522-8b78-48e4863848c9","order_by":1,"name":"Ben HELLER","email":"","orcid":"","institution":"Sheffield Hallam University","correspondingAuthor":false,"prefix":"","firstName":"Ben","middleName":"","lastName":"HELLER","suffix":""},{"id":283364022,"identity":"7095708e-bea7-4afb-8e05-4730c8a6adaf","order_by":2,"name":"Tom MADEN-WILKINSON","email":"","orcid":"","institution":"Advanced Wellbeing Research Centre (AWRC) Olympic Legacy Park","correspondingAuthor":false,"prefix":"","firstName":"Tom","middleName":"","lastName":"MADEN-WILKINSON","suffix":""},{"id":283364024,"identity":"e88e777e-7db1-46a4-bd6b-b51bdff9ebca","order_by":3,"name":"Nick HAMILTON","email":"","orcid":"","institution":"Sheffield Hallam University","correspondingAuthor":false,"prefix":"","firstName":"Nick","middleName":"","lastName":"HAMILTON","suffix":""}],"badges":[],"createdAt":"2024-03-24 16:44:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4158884/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4158884/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11332-024-01294-6","type":"published","date":"2024-12-01T15:57:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53662157,"identity":"7425aab1-e1e8-4fb1-a954-4fce6cd2d2a2","added_by":"auto","created_at":"2024-03-28 16:16:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":53691,"visible":true,"origin":"","legend":"\u003cp\u003eImage showing the custom-made visual feedback system, and on-screen mannequin with reference line. The moving reference line turns orange (a) as a warning if within a range of 5° and then red if greater than 5° from the set coordinates\u003c/p\u003e","description":"","filename":"Fig1.Feedbacksystem.png","url":"https://assets-eu.researchsquare.com/files/rs-4158884/v1/e6bc9de0d9f346c0fe1f6653.png"},{"id":53662158,"identity":"89600e1d-3975-4d86-a991-6110b013e223","added_by":"auto","created_at":"2024-03-28 16:16:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":131847,"visible":true,"origin":"","legend":"\u003cp\u003eEccentric knee flexor peak torque (A), break torque angle (B), and bilateral limb difference (C) performance metrics for verbal feedback (n = 24) and software feedback (n = 24) conditions. Asterisks (*) indicate any significant differences between feedback conditions\u003c/p\u003e","description":"","filename":"Fig2.FeedbackPTBTAandBLD.png","url":"https://assets-eu.researchsquare.com/files/rs-4158884/v1/9fe7e6d6050889b6c6fcfe28.png"},{"id":53662156,"identity":"48109b9e-4417-4634-88a1-2d78788da7aa","added_by":"auto","created_at":"2024-03-28 16:16:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":119566,"visible":true,"origin":"","legend":"\u003cp\u003eAngular velocity of the knee joint (A) and relative trunk-to-thigh angle (B) at peak torque technique metrics for verbal feedback (n = 24) and software feedback (n = 24) conditions. Asterisks (*) indicate any significant differences between feedback conditions\u003c/p\u003e","description":"","filename":"Fig3.FeedbackAVKandRTA.png","url":"https://assets-eu.researchsquare.com/files/rs-4158884/v1/dec994de345da08fda96d235.png"},{"id":70382759,"identity":"62e3b866-33ca-4685-8f6e-acd6ab8b688d","added_by":"auto","created_at":"2024-12-02 16:30:27","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":745532,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4158884/v1/64dcb752-a64a-40c2-91c3-14b713abc9e6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Examining the effect of verbal feedback vs. real-time software feedback on kinetic and kinematic metrics of the Nordic hamstring exercise","fulltext":[{"header":"Introduction","content":"\u003cp\u003eA conventional Nordic hamstring exercise (NHE) is performed with an athlete assuming a kneeling start position, with the hips fully extended and the torso held upright and rigid [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. From this position, athletes perform a controlled forward rotation action about the knee. In the majority of studies, athletes are informed to gradually lean forward at the slowest possible speed, maximally resisting the forward-falling movement with both legs, whilst holding the hips fixed in line with the knee and shoulder joints throughout the range of movement, keeping a neutral position throughout [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Factors affecting the quality of an NHE trial include having a distinct peak torque, maintaining a neutral hip flexion angle and performing a controlled descent speed [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Previous work by Sconce et al. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] reported poor overall NHE exercise technique and high intrasubject variability for both relative trunk-to-thigh angle at peak-torque (RTA) (\u003cem\u003erange\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.4\u0026ndash;44.7\u0026deg;), and angular velocity of the knee at peak-torque (AVK) (\u003cem\u003erange\u0026thinsp;=\u003c/em\u003e\u0026thinsp;3.6\u0026ndash;93.4deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) in 127 NHE trials (n\u0026thinsp;=\u0026thinsp;18).\u003c/p\u003e \u003cp\u003ePoor NHE technique can be problematic as excessive hip flexion produces larger NHE torque values at the same knee angle compared to a neutral hip position, which can lead to unreliable results between groups. This is due to the increased lever arm of the centre of mass about the knee joint axis influencing the torque-length relationship, increasing the resultant torque [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Therefore, the hip flexion angle should be controlled to allow accurate comparison between athletes [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Increasing hip flexion lengthens hamstring musculature, as observed in razor curl training [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] however this exercise does not allow for a break-point, which is required for assessing the length of the muscle at which failure occurs. Conversely, hip angular acceleration (\u0026lsquo;breaking\u0026rsquo; at the hip) reduces the knee flexor torque required to achieve a specific knee angle. In the current literature, NHE descent speed has generally been assessed visually and enforced through verbal instruction; using a very slow approach throughout the active range of motion (ROM) or descending to an average cadence of 30deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e using a metronome [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. AVK influences resultant torque, due to a shift of the torque-velocity relationship and also results in less time for the knee flexors to decelerate and control the forward action. This reduces time-under tension (TUT) which is important in NHE training for hypertrophy, specific muscle fibre recruitment, muscular endurance, metabolic stress, and motor unit activation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A controlled descent ensuring a maximal break-point is important for determining accurate muscle torque-length capabilities of the knee flexors, such as break-torque angle (BTA). The controlled descent focuses directly on optimising recruitment of the hamstring muscle complex for preventing strain injury risk, rather than the accessory muscles of the gluteus maximus, gastrocnemius, erector spinae, and adductors [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Furthermore, as suggested by Alt and Schmidt [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] poor NHE execution may impede or even prevent adaptations at long hamstring muscle lengths occurring at extended knee angles.\u003c/p\u003e \u003cp\u003eFew studies have considered exercise technique whilst performing the NHE. Alt and Schmidt [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] have proposed clear NHE training execution quality criteria (ANHEQ), recommending that NHEs should be executed with a constant knee extension velocity of 15deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e across the largest possible knee ROM (in a supramaximal unassisted NHE this would be up until \u0026lsquo;break-point\u0026rsquo;) with a suggested time under tension of ~\u0026thinsp;6.5 seconds per repetition. Moreover, they propose the eccentric phase of the NHE should be performed with minimal hip flexion, keeping the hands situated close to the shoulders, which is typical in the majority of the research [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This provides useful recommendation targets for NHE-assisted training; however, as found by Sconce et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] is difficult to implement for supramaximal NHE testing. We propose that integrating a software feedback system for testing can standardise NHE trials [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Moreover, controlling RTA and AVK (up until break-point) will provide consistent data, ensuring injury risk metrics (eccentric knee flexor peak torque and BTA) can be reliably reproduced between groups of athletes.\u003c/p\u003e \u003cp\u003eIt is well recognised that performance can be improved by augmented feedback (feedback from an external source provided as knowledge of performance or result) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This type of feedback is often used during resistance training to enhance acute physical performance and has shown promise as a method for improving chronic physical adaptation [\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, in a systematic review and meta-analysis by Weakley et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] it is reported that the magnitude of the response and the optimal method with which feedback is provided is inconsistent between studies. The application of visual and/or verbal augmented feedback, and more recently feedback through visual and/or audible applications (apps) can help increase the rate of learning which may reduce some injury risk factors [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Feedback has been shown to significantly increase eccentric knee flexion force output when traditionally measured on isokinetic dynamometry [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Most current hamstring testing and training devices offer kinetic feedback in the form of live graphical representation of force or torque traces using integrated dashboard software [\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], with results stored on a centralised cloud data storage and analytics platform. Results can be seen in real-time with immediate feedback for metrics such as bilateral hamstring strength, between-limb strength imbalances, and average strength across repetitions [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMost studies have only used verbal researcher encouragement or a metronome to control hip flexion and descent speed, rather than specific computer feedback. Few studies have used visual NHE feedback [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], and very limited studies [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] have studied the effect of feedback on NHE metrics, and none to our knowledge examining the effect of \u003cem\u003eboth\u003c/em\u003e kinetic and kinematic feedback on NHE exercise technique metrics. The study by Chalker et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] examined the effect real-time visual dashboard software feedback had on NHE force outputs and kinetic metrics such as eccentric knee flexor strength and bilateral force production between limb asymmetries [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. They reported that when feedback was provided on a hamstring testing device there was a significant increase in mean peak force production (mean diff. 21.7N) and no significant difference between limb asymmetry for feedback or no feedback (mean diff 5.7%). The increase in force production with feedback was attributed to an increased weaker limb force contribution compared to the stronger limb (mean diff 15.0N). However, there is little other published literature available regarding the influence of software feedback on NHE kinetic or kinematic metrics. Alt and Schmidt [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] state that for NHE intervention studies, standard training procedures should specify a constant target movement speed to obtain reliable results, and it is recommended to use a monitor to provide angle-time information in real-time to participants. This study aims to develop a novel, robust visual feedback NHE execution technique system and examine its effect on injury risk and technique metrics. The objective is to integrate a software system within the existing HA\u003cem\u003eL\u003c/em\u003eHAM\u0026deg; device [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] to monitor hip position and knee extension speed. It is hypothesised that software feedback will improve exercise technique.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eTwenty-four recreationally active participants (n\u0026thinsp;=\u0026thinsp;24) of varying NHE training experience, gender, and age were recruited to participate in this study (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD age 29\u0026thinsp;+\u0026thinsp;11 years, height 177\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3cm, and body mass 78.6\u0026thinsp;\u0026plusmn;\u0026thinsp;14.1kg). With exercise technique being the feedback focus, and this being explanatory research, a diverse representation of participants was chosen to offer a more holistic understanding of technique challenges and the impact of feedback. All participants completed an initial questionnaire, used to gather data medical and injury data. Exclusion criteria included a lower extremity injury in the previous 6 months, or a history of recurrent low-back, hip, thigh, or knee injuries. Furthermore, all participants self-declared as being physically fit and free from any health or medical conditions that would contraindicate or impede them from performing maximal NHE testing. After having all procedures explained to them, participants provided written informed consent to participate in the spirit of the Helsinki Declaration, before testing commenced. Ethical approval for the study was approved by the Universities Ethics Committee.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eExperimental protocol/Design\u003c/h2\u003e \u003cp\u003eThe HA\u003cem\u003eL\u003c/em\u003eHAM\u0026deg; NHE custom device developed by Sconce et al. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] was used to collect the data. Strain gauge load cells (DYMH-103 Micro Miniature Load Cell) measured individual right and left limb forces, and the software displayed these and combined limb total forces as force-time traces in line graph format. Torque was calculated for each NHE trial from the force measured by the load cells and the distance measured from the set pivot point (0.661m). Participants\u0026rsquo; NHE starting position was determined by lining up the lateral femoral epicondyle of the femur with the pivot point before commencement [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. An IMU (MOT1101_0, Phidgets Inc, Calgary, Canada) was positioned on a custom-made plastic carrier with pointed ends to help align the sensor laterally on the upper leg at an equal distance away from the greater trochanter and lateral femoral epicondyle. The IMU trunk sensor was also positioned laterally at an equal distance from the greater trochanter to the shoulder bursa. For the verbal feedback (VF) condition the researcher instructed participants to gradually lean forward at the slowest possible speed maintaining a neutral trunk alignment with the hips fixed in line with the knee and shoulder joints [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], whilst holding the hands in line with the shoulders, palms facing forward. Avoidance of hyperextension was advised. Participants were asked to perform the Nordic action until they could no longer withstand the torque around their knee flexors, using their hands to buffer the fall onto a fixed platform [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe software feedback (SF) was a custom-made visual system using an on-screen mannequin representation of a person and a pre-determined reference line to provide visual cues for the user (\u003cb\u003eFig.\u0026nbsp;1\u003c/b\u003e). The IMU sensors tracked the user\u0026rsquo;s knee and hip flexion angles in real time and used these to animate the mannequin. The superimposed dynamic reference line extended from the mannequin\u0026rsquo;s lateral epicondyle through the greater trochanter, to the shoulder bursa. Speed was set at 20deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e which was determined from previous work [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and is comparative to the NHE velocity used in the literature [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Hip flexion was set at 0\u0026deg; to encourage a neutral position throughout the range of motion. As the user performed the NHE action, they were prompted to match the movement of the reference line with the virtual representation on-screen. A monitor was positioned on a stand on the floor, at the base of the HA\u003cem\u003eL\u003c/em\u003eHAM\u0026deg; platform to suit the eye-line position. The grey reference line warned the user of deviation from the set optimal hip angle and speed by turning orange as a warning if within a range of 5\u0026deg; and then red if greater than 5\u0026deg; from the set coordinates (\u003cb\u003eFig.\u0026nbsp;1\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eRaw IMU data was acquired on a personal computer via a Phidget Bridge data acquisition board (Phidgets Inc., Calgary, Canada). The IMU data were converted into angles using a custom-coded program implementing a complementary filter and then exported in .CSV format. Using MATLAB R2020b software (MathWorks, Inc., Natick, MA) the following variables were subsequently calculated using a custom script:\u003c/p\u003e \u003cp\u003eInjury risk metrics as proposed in Sconce et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003ePeak torque\u003c/em\u003e\u0026thinsp;~\u0026thinsp;NHE bilateral maximum torque value.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eBreak-torque angle\u003c/em\u003e (BTA)\u0026thinsp;~\u0026thinsp;representing the knee and corresponding thigh angle at the instant that peak torque occurred. Full extension is represented as 180 degrees.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eBilateral limb torque difference\u003c/em\u003e (BLD)\u0026thinsp;~\u0026thinsp;representing the percentage difference between the right and left leg maximum torque values.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eExercise technique metrics as proposed in Sconce et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eRelative trunk-to-thigh angle\u003c/em\u003e (RTA)\u0026thinsp;~\u0026thinsp;the angle in the sagittal plane between the thigh and the trunk throughout the NHE ROM, representing hip angle. RTA at peak torque was then determined.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eAngular velocity of the knee joint\u003c/em\u003e (AVK)\u0026thinsp;~\u0026thinsp;representing the angular velocity of the knee joint throughout the NHE ROM, filtered using an 11-point average. AVK at peak torque was then determined.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eTrials\u003c/h2\u003e \u003cp\u003ePrior to performing the trials participants were instructed to perform an individual warm-up by using a stationary bike or rower for 3\u0026ndash;5 minutes and completing dynamic movements such as arm and hip circles, leg swings, heel-to-toe walks, knee hugs, walking lunges, and squats (2 sets of 10 repetitions). A crossover randomised design was used so that all participants received verbal instruction \u003cem\u003eand\u003c/em\u003e real-time software feedback on NHE technique over 2 separate sets of 3 maximal repetitions (6 maximal repetitions overall). The rest period between repetitions was long enough to allow the participant to comfortably recover for the next maximal effort and was advised as ~\u0026thinsp;6s [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The rest period between feedback types was substantial, at least 15 minutes, allowing for complete recovery. The order of performing the feedback (either VF or SF first) was randomised between participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003e144 trials from 24 participants (n\u0026thinsp;=\u0026thinsp;24) were initially considered (72 trials for each feedback condition). Data from the HA\u003cem\u003eL\u003c/em\u003eHAM\u0026deg; IMU\u0026rsquo;s were treated in MATLAB R2020b software (MathWorks, Inc., Natick, MA) and the data was subsequently statistically processed in GraphPad Prism 8.43 (GraphPad Software Inc). Trial exclusion criteria were no clear peak in the force-time trace, an extended flattened period, or no clear torque drop-off period; no trials were rejected. Descriptive statistics for all trials were calculated and reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Normality of data was confirmed using an appropriate test (Shapiro-Wilk) and a visual check of a Quantile-Quantile plot. The average of each participant\u0026rsquo;s 3 trials was calculated, and multiple independent t-tests were performed to compare differences in each metric between feedback conditions (VF and SF). Metrics compared were peak eccentric knee flexor torque (Nm), BTA (\u0026deg;), BLA (%), RTA (\u0026deg;) at peak torque, and AVK (deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) at peak torque. Where appropriate, effect sizes were calculated by Cohen \u003cem\u003ed\u003c/em\u003e and interpreted as small (d\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;0.2), moderate (d\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;0.5), and large (d\u0026thinsp;\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e\u0026ge;\u003c/span\u003e\u0026thinsp;0.8) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eInjury risk factor metrics\u003c/h2\u003e \u003cp\u003eChanges in mean peak torque, BLD, and BTA with feedback type can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eand Fig.\u0026nbsp;2\u003c/b\u003e. Feedback type significantly affected eccentric knee flexor peak torque (d\u0026thinsp;=\u0026thinsp;0.238 (\u003cem\u003eSmall\u003c/em\u003e), p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) which lowered when the NHE was performed with SF showing a mean decrease of 7.1Nm compared to VF. Altering feedback had no significant effect on BLD (d\u0026thinsp;=\u0026thinsp;0.068, p\u0026thinsp;=\u0026thinsp;0.578) or BTA (d\u0026thinsp;=\u0026thinsp;0.159, p\u0026thinsp;=\u0026thinsp;0.115).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eExercise technique metrics\u003c/h2\u003e \u003cp\u003eRTA and AVK changes with feedback can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e. RTA significantly decreased with SF (d\u0026thinsp;=\u0026thinsp;0.514 (\u003cem\u003eModerate\u003c/em\u003e), p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) showing a mean decrease of 5.7\u0026deg; compared to VF. AVK significantly decreased with SF (d\u0026thinsp;=\u0026thinsp;0.825 (\u003cem\u003eLarge\u003c/em\u003e), p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) showing a mean decrease of 8.7deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e compared to VF.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, and range reported for each metric per feedback condition (n\u0026thinsp;=\u0026thinsp;24)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eVerbal Feedback\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eSoftware Feedback\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetrics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003cp\u003e(Min-Max)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003cp\u003e(Min-Max)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKinetics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeak torque (Nm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.7\u0026thinsp;\u0026plusmn;\u0026thinsp;31.4*\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.7\u0026ndash;148.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72.6\u0026thinsp;\u0026plusmn;\u0026thinsp;27.9*\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.2\u0026ndash;142.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKinematics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBLD (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9\u0026ndash;30.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.2\u0026ndash;29.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBTA (\u0026deg;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102.0\u0026ndash;141.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e106.5\u0026ndash;146.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRTA (\u0026deg;) at peak-torque\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.1\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2*\u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.7\u0026ndash;57.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7* \u003csup\u003e\u003cem\u003eb\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.3\u0026ndash;34.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAVK (deg\u0026middot;s\u003csup\u003e-1\u003c/sup\u003e) at peak-torque\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.5*\u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.8\u0026ndash;61.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9* \u003csup\u003e\u003cem\u003ec\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.5\u0026ndash;26.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNm Newton-metre, % percentage difference, \u0026deg; degrees, deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e degrees per second\u003c/p\u003e \u003cp\u003eBLD Bilateral limb torque difference, BTA Break-torque angle, RTA Relative trunk-to-thigh angle, AVK Angular velocity of the knee\u003c/p\u003e \u003cp\u003e \u003csup\u003e \u003cem\u003e*\u003c/em\u003e \u003c/sup\u003e \u003cem\u003edenotes a significant difference between VF and SF (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01)\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003cp\u003ea denotes a small effect size\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003cp\u003eb denotes medium effect size\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section4\"\u003e \u003cp\u003ec denotes large effect size\u003c/p\u003e "},{"header":"Discussion","content":"\u003cp\u003eThe findings affirm the hypothesis that SF enhances acute NHE exercise quality, agreeing with the systematic review findings by Weakley et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. They reported that resistance training feedback has a positive influence on immediate performance and can improve favourable adaptations over the long term. Both technique metrics significantly improved (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e) however, performance metrics demonstrated either no significant change or a negatively impacted significant effect with SF (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eand Fig.\u0026nbsp;2\u003c/b\u003e). BLD percentage and BTA showed no significant change between feedback conditions and peak torque significantly decreased with SF by a mean decrease of 7.1 Nm compared to VF. This is unsurprising, however, as it is known that a controlled NHE action (neutral hip and slower) will left-ward shift the torque-length and torque-velocity relationships [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Moreover, the SF was intentionally confined to modify NHE hip flexion and speed exclusively, and not injury risk factor metrics. Interestingly the upper ranges dropped significantly (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e) with SF for both RTA (57.9\u0026deg; to 34.6\u0026deg;) and AVK (61.6 deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to 26.7 deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e), which suggests that individuals initially exhibiting poorer exercise technique showed the most improvement, bringing them closer to the normal ranges.\u003c/p\u003e \u003cp\u003eThe literature shows the impact of different hamstring exercises on muscle architecture and morphology and the implications this can have for injury prevention [\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Notably, both the NHE and hip extension exercises stimulate significant increases in Biceps femoris long head (BFlh) fascicle length, however, the NHE is reported to be more effective in promoting hypertrophy in the BFlh [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Furthermore, a study by Baumgart et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] reported that parametric and angle-specific flexion and extension torques differ according to hip flexion, velocity, and muscle contraction mode. Hamstring muscles operate differently across different lengths in response to changing exercise stimuli [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] and studies have suggested that injury is associated with a left-ward shift of peak torque to shorter angle lengths in the hamstrings [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The evaluation of the torque-angle relationship may be a useful tool for predicting hamstring strain injuries and as a return-to-play measure [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Therefore, standardized, controlled technique of exercises that measure torque-angular data is important, as a deviation of form can alter the intended nature of the exercise, impacting the desired adaptations in the knee flexors, whether for training, angle-specific testing, performance optimisation, injury prevention or rehabilitation.\u003c/p\u003e \u003cp\u003eChalker et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] reported an increase in mean peak force production when using feedback, however it was specific to force-time traces on a screen and not hip and knee angles, or movement velocity. Moreover, if increased torque is a result of suboptimal exercise technique, there is a risk of overestimation which has implications in hamstring training intervention studies where precise quantification of change is important for assessing the effectiveness of the intervention [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Additionally, the production of peak torque within a shorter muscle length range is less useful for targeting the site of hamstring injuries [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. It is, therefore, reasonable to hypothesise that integrating SF into chronic NHE training, using a moving reference line on-screen and supplementing it with the option to visualise torque-time traces and break-point failures as part of a performance/injury-risk software mode would be beneficial.\u003c/p\u003e \u003cp\u003eSeveral advantages of the biofeedback system include immediate user correction, engagement, and better exercise technique. The system reinforces proper NHE form by visually guiding users through the correct range of motion and pace. Real-time feedback helps avoid overextension or rapid movements that could lead to strain. As users receive immediate visual cues, they can make adjustments allowing them to course-correct during the exercise. The visual representation and reference line create an interface experience, encouraging users to maintain focus and adherence, which is a major issue in NHE compliance [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. It is suggested that acute feedback is most beneficial when of high frequency (during every rep), and of a visual kinematic nature [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] which the HA\u003cem\u003eL\u003c/em\u003eHAM\u0026deg; SF system offers.\u003c/p\u003e \u003cp\u003eLimitations of the study are relatively modest sample numbers, and the absence of a separate pre-testing familiarisation phase as noted in Alt and Schmidt [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Nonetheless, our focus examined changes in metrics with SF rather than preparing athletes for exhaustive performance testing or training. User feedback recommended that the reference line start from a position behind neutral, featuring an initial slightly flexed knee position with a \u0026lsquo;preliminary movement phase\u0026rsquo; to allow the user to adjust to the pace before passing through the neutral position. As a result, the test is then initiated in a manner that ensures a controlled and smoother commencement. Another consideration for SF adjustment would be defining an anatomically aligned hip flexion angle reflecting natural physiological curvature of the lumbar spine, within a permissible range of up to 20\u0026deg; as suggested by, Alt and Schmidt [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This modification would expand the cautionary orange range to encompass values up to this threshold and subsequently set the red range beyond it. Alt and Schmidt [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] recommend NHEs should be executed with a constant knee extension velocity of 15deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e across the NHE range of motion, with a 10deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e deviation of this being classed as the break-point (failure). Again, setting a cautionary range for AVK of between 15\u0026ndash;25 deg\u0026middot;s\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e should be explored in future work.\u003c/p\u003e \u003cp\u003eImplementing a flexible SF system for NHE training where the individual could customise the AVK and RTA threshold, would be advisable. This would support the required muscle adaptations required for personalised hamstring training. For instance, faster eccentric loading velocity could be advantageous for recruiting higher hamstring muscle activation [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], whereas a slower velocity with controlled hip flexion might be preferable for optimising TUT, without using the accessory muscles to maximise the preferential protective adaptations of hypertrophy and longer BFlh fascicle length required for HSI prevention. Ongoing user familiarisation of the feedback system over the long term would be required to evaluate its effectiveness for this type of purpose.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe HA\u003cem\u003eL\u003c/em\u003eHAM\u0026deg; integrated SF system significantly improves acute NHE technique (RTA and AVK), benefitting individuals initially exhibiting poorer technique the most. A customizable SF system with a performance mode option may be beneficial for NHE chronic intervention training and testing to elicit desired protective muscular adaptations and lower hamstring strain injury risk.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAVK \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Angular velocity of the knee joint\u003c/p\u003e\n\u003cp\u003eBFlh \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Biceps femoris long head\u003c/p\u003e\n\u003cp\u003eBLD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Bilateral limb difference\u003c/p\u003e\n\u003cp\u003eBTA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Break-torque angle\u003c/p\u003e\n\u003cp\u003eHSI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Hamstring strain injury\u003c/p\u003e\n\u003cp\u003eNHE \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Nordic hamstring exercise\u003c/p\u003e\n\u003cp\u003eRTA \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Relative trunk-to-thigh angle \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSF \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Software feedback\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTUT\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Time-under-tension\u003c/p\u003e\n\u003cp\u003eVF \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Verbal feedback \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure of interest:\u003c/strong\u003e The authors report no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u0026nbsp;\u003c/strong\u003eInformed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish:\u0026nbsp;\u003c/strong\u003eParticipants signed informed consent regarding publishing their data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e No funding was received for conducting this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval:\u0026nbsp;\u003c/strong\u003eThe study was performed in line with the principles of the Declaration of Helsinki.\u0026nbsp;Ethical approval for the study\u0026nbsp;was approved by the Sheffield Hallam University Ethics Committee (Date: 24/03/2021/No ER29609708).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e The data that support the findings of this study are available from the corresponding author, [ES], upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contribution statement\u003c/strong\u003e: \u003cstrong\u003e\u003cem\u003e:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eES, BH, TMW and NH were responsible for the conception of the study. NH and BH were responsible for the design and implementation of the device hardware and software. ES was involved in the data collection and conducted the analyses. ES drafted the manuscript, which was critically revised by the coauthors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePetersen J, Thorborg K, Nielsen MB, et al (2011) Preventive effect of eccentric training on acute hamstring injuries in men\u0026rsquo;s soccer: A cluster-randomized controlled trial. Am J Sports Med 39:2296\u0026ndash;2303. https://doi.org/10.1177/0363546511419277\u003c/li\u003e\n\u003cli\u003eMj\u0026oslash;lsnes R, Arnason A, \u0026Oslash;sthagen T, et al (2004) A 10-week randomized trial comparing eccentric vs. concentric hamstring strength training in well-trained soccer players. 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BMC Sports Sci Med Rehabil 14:1\u0026ndash;34. https://doi.org/10.1186/s13102-022-00555-6\u003c/li\u003e\n\u003cli\u003eBrockett CL, Morgan DL, Proske U (2004) Predicting hamstring injury in elite athletes. Med Sci Sports Exerc 36:379\u0026ndash;387. https://doi.org/10.1249/01.MSS.0000117165.75832.05\u003c/li\u003e\n\u003cli\u003eBrughelli M, Cronin J (2007) Altering the length-tension relationship with eccentric exercise: Implications for performance and injury. Sport Med 37:807\u0026ndash;826. https://doi.org/10.2165/00007256-200737090-00004\u003c/li\u003e\n\u003cli\u003eAmundsen R, M\u0026oslash;ller M, Bahr R (2023) Performing Nordic hamstring strength testing with additional weight affects the maximal eccentric force measured: do not compare apples to oranges. BMJ Open Sport Exerc Med 9:1\u0026ndash;6. https://doi.org/10.1136/bmjsem-2023-001699\u003c/li\u003e\n\u003cli\u003eHorst N Van Der, Hoef S Van De, Otterloo P Van, Klein M (2021) Effective but not adhered to: how can we improve adherence to evidence-based hamstring injury prevention in amateur football? 31:42\u0026ndash;48\u003c/li\u003e\n\u003cli\u003eZehr EP, Sale DG (1994) Ballistic movement: Muscle activation and neuromuscular adaptation. Can J Appl Physiol 19:363\u0026ndash;378. https://doi.org/10.1139/h94-030\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":"sport-sciences-for-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssfh","sideBox":"Learn more about [Sport Sciences for Health](http://link.springer.com/journal/11332)","snPcode":"11332","submissionUrl":"https://submission.nature.com/new-submission/11332/3","title":"Sport Sciences for Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Nordic hamstring exercise, software feedback, technique","lastPublishedDoi":"10.21203/rs.3.rs-4158884/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4158884/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eA wealth of research exists for the Nordic hamstring exercise, and several devices provide real-time feedback on torque profiling. However, none currently offer feedback on technique execution. This study investigated the effect of verbal and software feedback on Nordic exercise kinetic and kinematic metrics.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e24 recreational participants completed 3 bilateral repetitions per feedback condition on a hamstring testing device. Hamstring strain injury risk metrics (peak torque, break-torque angle, bilateral limb percentage difference) and exercise technique metrics (relative trunk-to-thigh angle, angular velocity of the knee) were recorded for analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFeedback type significantly affected eccentric knee flexor peak torque, by a mean decrease of 7.1 Nm when performed with software feedback (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.238, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Altering feedback had no significant effect on bilateral limb difference percentage (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.068, p\u0026thinsp;=\u0026thinsp;0.578) or break-torque angle (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.159, p\u0026thinsp;=\u0026thinsp;0.115). Software feedback significantly decreased the mean of both the relative-trunk-to-thigh angle at peak torque by 5.7\u0026deg; (Cohen\u0026rsquo;s d\u0026thinsp;=\u0026thinsp;0.514, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and the angular velocity of the knee at peak torque by 8.7 deg\u0026middot;s-1.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAn integrated software feedback system significantly improves acute Nordic exercise technique, benefitting individuals initially exhibiting poorer technique the most.\u003c/p\u003e","manuscriptTitle":"Examining the effect of verbal feedback vs. real-time software feedback on kinetic and kinematic metrics of the Nordic hamstring exercise","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-28 16:16:24","doi":"10.21203/rs.3.rs-4158884/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-29T16:12:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-24T14:43:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"25411794856175304137754110451429219796","date":"2024-08-22T07:32:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-02T18:11:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-25T02:11:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-25T02:11:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Sport Sciences for Health","date":"2024-03-24T16:39:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"sport-sciences-for-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssfh","sideBox":"Learn more about [Sport Sciences for Health](http://link.springer.com/journal/11332)","snPcode":"11332","submissionUrl":"https://submission.nature.com/new-submission/11332/3","title":"Sport Sciences for Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"e2c7ca46-8642-4882-8421-98bccfb46402","owner":[],"postedDate":"March 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-12-02T16:02:02+00:00","versionOfRecord":{"articleIdentity":"rs-4158884","link":"https://doi.org/10.1007/s11332-024-01294-6","journal":{"identity":"sport-sciences-for-health","isVorOnly":false,"title":"Sport Sciences for Health"},"publishedOn":"2024-12-01 15:57:31","publishedOnDateReadable":"December 1st, 2024"},"versionCreatedAt":"2024-03-28 16:16:24","video":"","vorDoi":"10.1007/s11332-024-01294-6","vorDoiUrl":"https://doi.org/10.1007/s11332-024-01294-6","workflowStages":[]},"version":"v1","identity":"rs-4158884","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4158884","identity":"rs-4158884","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}