Real-time feedback by wearables in running: Current approaches, challenges and suggestions for improvements

Impact of Running Clothes on Accuracy of Smartphone-Based 2D Joint Kinematic Assessment During Treadmill Running Using OpenPifPaf

The assessment of running kinematics is essential for injury prevention and rehabilitation, including anterior cruciate ligament sprains. Recent advances in computer vision have enabled the development of tools for quantifying kinematics in research and clinical settings. This study evaluated the accuracy of an OpenPifPaf-based markerless method for assessing sagittal plane kinematics of the ankle, knee, and hip during treadmill running using smartphone video footage and examined the impact of clothing on the results. Thirty healthy participants ran at 2.5 and 3.6 m/s under two conditions: (1) wearing minimal clothing with markers to record kinematics by using both a smartphone and a marker-based system, and (2) wearing usual running clothes and recording kinematics by only using a smartphone. Joint angles, averaged over 20 cycles, were analysed using SPM1D and RMSE. The markerless method produced kinematic waveforms closely matching the marker-based results, with RMSEs of 5.6° (hip), 3.5° (ankle), and 2.9° (knee), despite some significant differences identified by SPM1D. Clothing had minimal impact, with RMSEs under 2.8° for all joints. These findings highlight the potential of the OpenPifPaf-based markerless method as an accessible, simple, and reliable tool for assessing running kinematics, even in natural attire, for research and clinical applications.

Immersive virtual reality for learning exoskeleton-like virtual walking: a feasibility study

PURPOSE

Virtual Reality (VR) has proven to be an effective tool for motor (re)learning. Furthermore, with the current commercialization of low-cost head-mounted displays (HMDs), immersive virtual reality (IVR) has become a viable rehabilitation tool. Nonetheless, it is still an open question how immersive virtual environments should be designed to enhance motor learning, especially to support the learning of complex motor tasks. An example of such a complex task is triggering steps while wearing lower-limb exoskeletons as it requires the learning of several sub-tasks, e.g., shifting the weight from one leg to the other, keeping the trunk upright, and initiating steps. This study aims to find the necessary elements in VR to promote motor learning of complex virtual gait tasks.

METHODS

In this study, we developed an HMD-IVR-based system for training to control wearable lower-limb exoskeletons for people with sensorimotor disorders. The system simulates a virtual walking task of an avatar resembling the sub-tasks needed to trigger steps with an exoskeleton. We ran an experiment with forty healthy participants to investigate the effects of first- (1PP) vs. third-person perspective (3PP) and the provision (or not) of concurrent visual feedback of participants' movements on the walking performance - namely number of steps, trunk inclination, and stride length -, as well as the effects on embodiment, usability, cybersickness, and perceived workload.

RESULTS

We found that all participants learned to execute the virtual walking task. However, no clear interaction of perspective and visual feedback improved the learning of all sub-tasks concurrently. Instead, the key seems to lie in selecting the appropriate perspective and visual feedback for each sub-task. Notably, participants embodied the avatar across all training modalities with low cybersickness levels. Still, participants' cognitive load remained high, leading to marginally acceptable usability scores.

CONCLUSIONS

Our findings suggest that to maximize learning, users should train sub-tasks sequentially using the most suitable combination of person's perspective and visual feedback for each sub-task. This research offers valuable insights for future developments in IVR to support individuals with sensorimotor disorders in improving the learning of walking with wearable exoskeletons.

Predicting Musculoskeletal Loading at Common Running Injury Locations Using Machine Learning and Instrumented Insoles

INTRODUCTION

Wearables have the potential to provide accurate estimates of tissue loads at common running injury locations. Here we investigate the accuracy by which commercially available instrumented insoles (ARION; ATO-GEAR, Eindhoven, The Netherlands) can predict musculoskeletal loading at common running injury locations.

METHODS

Nineteen runners (10 males) ran at five different speeds, four slopes, with different step frequencies, and forward trunk lean on an instrumented treadmill while wearing instrumented insoles. The insole data were used as input to an artificial neural network that was trained to predict the Achilles tendon strain, and tibia and patellofemoral stress impulses and weighted impulses (damage proxy) as determined with musculoskeletal modeling. Accuracy was investigated using leave-one-out cross-validation and correlations. The effect of different input metrics was also assessed.

RESULTS

The neural network predicted tissue loading with overall relative percentage errors of 1.95 ± 8.40%, -7.37 ± 6.41%, and -12.8 ± 9.44% for the patellofemoral joint, tibia, and Achilles tendon impulse, respectively. The accuracy significantly changed with altered running speed, slope, or step frequency. Mean (95% confidence interval) within-individual correlations between modeled and predicted impulses across conditions were generally nearly perfect, being 0.92 (0.89 to 0.94), 0.95 (0.93 to 0.96), and 0.95 (0.94 to 0.96) for the patellofemoral, tibial, and Achilles tendon stress/strain impulses, respectively.

CONCLUSIONS

This study shows that commercially available instrumented insoles can predict loading at common running injury locations with variable absolute but (very) high relative accuracy. The absolute error was lower than the methods that measure only the step count or assume a constant load per speed or slope. This developed model may allow for quantification of in-field tissue loading and real-time tissue loading-based feedback to reduce injury risk.

Wearable Technology and Its Influence on Motor Development and Biomechanical Analysis

The convergence among biomechanics, motor development, and wearable technology redefines our understanding of human movement. These technologies allow for the continuous monitoring of motor development and the state of motor abilities from infancy to old age, enabling early and personalized interventions to promote healthy motor skills. For athletes, they offer valuable insights to optimize technique and prevent injuries, while in old age, they help maintain mobility and prevent falls. Integration with artificial intelligence further extends these capabilities, enabling sophisticated data analysis. Wearable technology is transforming the way we approach motor development and maintenance of motor skills, offering unprecedented possibilities for improving health, performance, and quality of life at every stage of life. The promising future of these technologies paves the way for an era of more personalized and effective healthcare, driven by innovation and interdisciplinary collaboration.

Clustering analysis across different speeds reveals two distinct running techniques with no differences in running economy

Establishing the links between running technique and economy remains elusive due to high inter-individual variability. Clustering runners by technique may enable tailored training recommendations, yet it is unclear if different techniques are equally economical and whether clusters are speed-dependent. This study aimed to identify clusters of runners based on technique and to compare cluster kinematics and running economy. Additionally, we examined the agreement of clustering partitions of the same runners at different speeds. Trunk and lower-body kinematics were captured from 84 trained runners at different speeds on a treadmill. We used Principal Component Analysis for dimensionality reduction and agglomerative hierarchical clustering to identify groups of runners with a similar technique, and we evaluated cluster agreement across speeds. Clustering runners at different speeds independently produced different partitions, suggesting single speed clustering can fail to capture the full speed profile of a runner. The two clusters identified using data from the whole range of speeds showed differences in pelvis tilt and duty factor. In agreement with self-optimisation theories, there were no differences in running economy, and no differences in participants' characteristics between clusters. Considering inter-individual technique variability may enhance the efficacy of training designs as opposed to 'one size fits all' approaches.

Sacroiliac Joint Dysfunction in Endurance Runners Using Wearable Technology as a Clinical Monitoring Tool: Systematic Review

BACKGROUND

In recent years, researchers have delved into the relationship between the anatomy and biomechanics of sacroiliac joint (SIJ) pain and dysfunction in endurance runners to elucidate the connection between lower back pain and the SIJ. However, the majority of SIJ pain and dysfunction cases are diagnosed and managed through a traditional athlete-clinician arrangement, where the athlete must attend regular in-person clinical appointments with various allied health professionals. Wearable sensors (wearables) are increasingly serving as a clinical diagnostic tool to monitor an athlete's day-to-day activities remotely, thus eliminating the necessity for in-person appointments. Nevertheless, the extent to which wearables are used in a remote setting to manage SIJ dysfunction in endurance runners remains uncertain.

OBJECTIVE

This study aims to conduct a systematic review of the literature to enhance our understanding regarding the use of wearables in both in-person and remote settings for biomechanical-based rehabilitation in SIJ dysfunction among endurance runners. In addressing this issue, the overarching goal was to explore how wearables can contribute to the clinical diagnosis (before, during, and after) of SIJ dysfunction.

METHODS

Three online databases, including PubMed, Scopus, and Google Scholar, were searched using various combinations of keywords. Initially, a total of 4097 articles were identified. After removing duplicates and screening articles based on inclusion and exclusion criteria, 45 articles were analyzed. Subsequently, 21 articles were included in this study. The quality of the investigation was assessed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) evidence-based minimum set of items for reporting in systematic reviews.

RESULTS

Among the 21 studies included in this review, more than half of the investigations were literature reviews focusing on wearable sensors in the diagnosis and treatment of SIJ pain, wearable movement sensors for rehabilitation, or a combination of both for SIJ gait analysis in an intelligent health care setting. As many as 4 (19%) studies were case reports, and only 1 study could be classified as fully experimental. One paper was classified as being at the "pre" stage of SIJ dysfunction, while 6 (29%) were identified as being at the "at" stage of classification. Significantly fewer studies attempted to capture or classify actual SIJ injuries, and no study directly addressed the injury recovery stage.

CONCLUSIONS

SIJ dysfunction remains underdiagnosed and undertreated in endurance runners. Moreover, there is a lack of clear diagnostic or treatment pathways using wearables remotely, despite the availability of validated technology. Further research of higher quality is recommended to investigate SIJ dysfunction in endurance runners and explore the use of wearables for rehabilitation in remote settings.

Rearfoot Strike Run Retraining for Achilles Tendon Pain: A Two-patient Case Series

INTRODUCTION

Running-related injuries are prevalent in the military and are often related to physical fitness test training. Non-rearfoot striking while running is known to increase the risk of Achilles tendon injuries because of the high eccentric energy absorption by the elastic components of the planarflexor muscle-tendon complex. However, there is limited evidence to suggest benefits of converting runners with Achilles tendon pain to use a rearfoot strike.

METHODS

This is a case series of two active-duty Service members with chronic, running-related Achilles tendon pain that utilized a natural non-rearfoot strike pattern. Both patients were trained to utilize a rearfoot strike while running through the use of real-time visual feedback from wearable sensors.

RESULTS

The trained rearfoot strike pattern was retained for over one month after the intervention, and both patients reported improvements in pain and self-reported function.

CONCLUSIONS

This case series demonstrated the clinical utility of converting two non-rearfoot strike runners to a rearfoot strike pattern to decrease eccentric demands on the plantarflexors and reduce Achilles tendon pain while running.

Artificial intelligence and Machine Learning approaches in sports: Concepts, applications, challenges, and future perspectives

BACKGROUND

The development and application of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare have gained attention as a promising and powerful resource to change the landscape of healthcare. The potential of these technologies for injury prediction, performance analysis, personalized training, and treatment comes with challenges related to the complexity of sports dynamics and the multidimensional aspects of athletic performance.

OBJECTIVES

We aimed to present the current state of AI and ML applications in sports science, specifically in the areas of injury prediction, performance enhancement, and rehabilitation. We also examine the challenges of incorporating AI and ML into sports and suggest directions for future research.

METHOD

We conducted a comprehensive literature review, focusing on publications related to AI and ML applications in sports. This review encompassed studies on injury prediction, performance analysis, and personalized training, emphasizing the AI and ML models applied in sports.

RESULTS

The findings highlight significant advancements in injury prediction accuracy, performance analysis precision, and the customization of training programs through AI and ML. However, future studies need to address challenges such as ethical considerations, data quality, interpretability of ML models, and the integration of complex data.

CONCLUSION

AI and ML may be useful for the prevention, detection, diagnosis, and treatment of health conditions. In this Masterclass paper, we introduce AI and ML concepts, outline recent breakthroughs in AI technologies and their applications, identify the challenges for further progress of AI systems, and discuss ethical issues, clinical and research opportunities, and future perspectives.

The Relationship Between Running Biomechanics and Running Economy: A Systematic Review and Meta-Analysis of Observational Studies

BACKGROUND

Running biomechanics is considered an important determinant of running economy (RE). However, studies examining associations between running biomechanics and RE report inconsistent findings.

OBJECTIVE

The aim of this systematic review was to determine associations between running biomechanics and RE and explore potential causes of inconsistency.

METHODS

Three databases were searched and monitored up to April 2023. Observational studies were included if they (i) examined associations between running biomechanics and RE, or (ii) compared running biomechanics between groups differing in RE, or (iii) compared RE between groups differing in running biomechanics during level, constant-speed, and submaximal running in healthy humans (18-65 years). Risk of bias was assessed using a modified tool for observational studies and considered in the results interpretation using GRADE. Meta-analyses were performed when two or more studies reported on the same outcome. Meta-regressions were used to explore heterogeneity with speed, coefficient of variation of height, mass, and age as continuous outcomes, and standardization of running shoes, oxygen versus energetic cost, and correction for resting oxygen or energy cost as categorical outcomes.

RESULTS

Fifty-one studies (n = 1115 participants) were included. Most spatiotemporal outcomes showed trivial and non-significant associations with RE: contact time r = - 0.02 (95% confidence interval [CI] - 0.15 to 0.12); flight time r = 0.11 (- 0.09 to 0.32); stride time r = 0.01 (- 0.8 to 0.50); duty factor r = - 0.06 (- 0.18 to 0.06); stride length r = 0.12 (- 0.15 to 0.38), and swing time r = 0.12 (- 0.13 to 0.36). A higher cadence showed a small significant association with a lower oxygen/energy cost (r = - 0.20 [- 0.35 to - 0.05]). A smaller vertical displacement and higher vertical and leg stiffness showed significant moderate associations with lower oxygen/energy cost (r = 0.35, - 0.31, - 0.28, respectively). Ankle, knee, and hip angles at initial contact, midstance or toe-off as well as their range of motion, peak vertical ground reaction force, mechanical work variables, and electromyographic activation were not significantly associated with RE, although potentially relevant trends were observed for some outcomes.

CONCLUSIONS

Running biomechanics can explain 4-12% of the between-individual variation in RE when considered in isolation, with this magnitude potentially increasing when combining different variables. Implications for athletes, coaches, wearable technology, and researchers are discussed in the review.

PROTOCOL REGISTRATION

https://doi.org/10.17605/OSF.IO/293 ND (OpenScience Framework).

The biomechanics of running and running styles: a synthesis

Running movements are parametrised using a wide variety of devices. Misleading interpretations can be avoided if the interdependencies and redundancies between biomechanical parameters are taken into account. In this synthetic review, commonly measured running parameters are discussed in relation to each other, culminating in a concise, yet comprehensive description of the full spectrum of running styles. Since the goal of running movements is to transport the body centre of mass (BCoM), and the BCoM trajectory can be derived from spatiotemporal parameters, we anticipate that different running styles are reflected in those spatiotemporal parameters. To this end, this review focuses on spatiotemporal parameters and their relationships with speed, ground reaction force and whole-body kinematics. Based on this evaluation, we submit that the full spectrum of running styles can be described by only two parameters, namely the step frequency and the duty factor (the ratio of stance time and stride time) as assessed at a given speed. These key parameters led to the conceptualisation of a so-called Dual-axis framework. This framework allows categorisation of distinctive running styles (coined 'Stick', 'Bounce', 'Push', 'Hop', and 'Sit') and provides a practical overview to guide future measurement and interpretation of running biomechanics.

Effect of cross-slope angle on running economy and gait characteristics at moderate running velocity

PURPOSE

Outdoor running surfaces are designed with a cross-slope, which can alter kinetic and kinematic gait parameters. The purpose of this study was to evaluate running economy, gait characteristics, and muscle activation while running on a surface with cross-slopes similar to those encountered on roads and trails.

METHODS

Eleven recreational runners (females n = 6) completed 5-min running trials on a treadmill at 10 km h-1 with cross-slopes of 0, 1.15, 2.29, and 6 deg in a randomized order.

RESULTS

There were no significant differences in VO2, HR, RER, or VE across cross-slope conditions. Compared to 0 deg of cross-slope, ground contact time and duty factor increased at 2.29 and 6 deg, with significant decreases in absolute and relative flight times. Rear foot angles increased in the upslope leg at 2.29 and 6 deg cross-slopes and decreased in the downslope leg at 6 deg compared to 0 deg of cross-slope, with differences between legs for the 2.29 and 6 deg conditions. Knee flexion at foot strike increased in the upslope leg at a 6 deg cross-slope. Vastus lateralis, biceps femoris, gastrocnemius, and tibialis anterior activation were not affected by the cross-slope conditions. While cross-slopes up to 6 deg result in changes to some gait kinematics, these effects do not impact running economy at moderate running velocity.

Reliability of Xsens inertial measurement unit in measuring trunk accelerations: a sex-based differences study during incremental treadmill running

Introduction

Inertial measurement units (IMUs) are utilized to measure trunk acceleration variables related to both running performances and rehabilitation purposes. This study examined both the reliability and sex-based differences of these variables during an incremental treadmill running test.

Methods

Eighteen endurance runners performed a test-retest on different days, and 30 runners (15 females) were recruited to analyze sex-based differences. Mediolateral (ML) and vertical (VT) trunk displacement and root mean square (RMS) accelerations were analyzed at 9, 15, and 21 km·h-1.

Results

No significant differences were found between test-retests [effect size (ES)<0.50)]. Higher intraclass correlation coefficients (ICCs) were found in the trunk displacement (0.85-0.96) compared to the RMS-based variables (0.71-0.94). Male runners showed greater VT displacement (ES = 0.90-1.0), while female runners displayed greater ML displacement, RMS ML and anteroposterior (AP), and resultant euclidean scalar (RES) (ES = 0.83-1.9).

Discussion

The IMU was found reliable for the analysis of the studied trunk acceleration-based variables. This is the first study that reports different results concerning acceleration (RMS) and trunk displacement variables for a same axis in the analysis of sex-based differences.

The Effect of Wearable-Based Real-Time Feedback on Running Injuries and Running Performance: A Randomized Controlled Trial

BACKGROUND

Running technique and running speed are considered important risk factors for running injuries. Real-time feedback on running technique and running speed by wearables may help reduce injury risk.

PURPOSE

To investigate whether real-time feedback on spatiotemporal metrics and relative speed by commercially available pressure-sensitive insoles would reduce running injuries and improve running performance compared with no real-time feedback.

STUDY DESIGN

Randomized controlled trial; Level of evidence, 1.

METHODS

A total of 220 recreational runners were randomly assigned into the intervention and control groups. Both groups received pressure-sensitive insoles, but only the intervention group received real-time feedback on spatiotemporal metrics and relative speed. The feedback aimed to reduce loading on the joint/segment estimated to exhibit the highest load. Injury rates were compared between the groups using Cox regressions. Secondary outcomes compared included injury severity, the proportion of runners with multiple injuries, changes in self-reported personal best times and motivation (Behavioral Regulation in Exercise Questionnaire-2), and interest in continuing wearable use after study completion.

RESULTS

A total of 160 participants (73%) were included in analyses of the primary outcome. Intention-to-treat analysis showed no significant difference in injury rate between the groups (Hazard ratio [HR], 1.11; P = .70). This was expected, as 53 of 160 (33%) participants ended up in the unassigned group because they used incorrect wearable settings, nullifying any interventional effects. As-treated analysis showed a significantly lower injury rate among participants receiving real-time feedback (HR, 0.53; P = .03). Similarly, the first-time injury severity was significantly lower (-0.43; P = .042). Per-protocol analysis showed no significant differences in injury rates, but the direction favored the intervention group (HR, 0.67; P = .30). There were no significant differences in the proportion of patients with multiple injuries (HR, 0.82; P = .40) or changes in running performance (3.07%; P = .26) and motivation. Also, ~60% of the participants who completed the study showed interest in continuing wearable use.

CONCLUSION

Real-time feedback on spatiotemporal metrics and relative speed provided by commercially available instrumented insoles may reduce the rate and severity of injuries in recreational runners. Feedback did not influence running performance and exercise motivation.

REGISTRATION

NL8472 (Dutch Trial Register).

A 0.05 m Change in Inertial Measurement Unit Placement Alters Time and Frequency Domain Metrics during Running

Inertial measurement units (IMUs) provide exciting opportunities to collect large volumes of running biomechanics data in the real world. IMU signals may, however, be affected by variation in the initial IMU placement or movement of the IMU during use. To quantify the effect that changing an IMU's location has on running data, a reference IMU was 'correctly' placed on the shank, pelvis, or sacrum of 74 participants. A second IMU was 'misplaced' 0.05 m away, simulating a 'worst-case' misplacement or movement. Participants ran over-ground while data were simultaneously recorded from the reference and misplaced IMUs. Differences were captured as root mean square errors (RMSEs) and differences in the absolute peak magnitudes and timings. RMSEs were ≤1 g and ~1 rad/s for all axes and misplacement conditions while mean differences in the peak magnitude and timing reached up to 2.45 g, 2.48 rad/s, and 9.68 ms (depending on the axis and direction of misplacement). To quantify the downstream effects of these differences, initial and terminal contact times and vertical ground reaction forces were derived from both the reference and misplaced IMU. Mean differences reached up to -10.08 ms for contact times and 95.06 N for forces. Finally, the behavior in the frequency domain revealed high coherence between the reference and misplaced IMUs (particularly at frequencies ≤~10 Hz). All differences tended to be exaggerated when data were analyzed using a wearable coordinate system instead of a segment coordinate system. Overall, these results highlight the potential errors that IMU placement and movement can introduce to running biomechanics data.

Comparing Self-Reported Running Distance and Pace With a Commercial Fitness Watch Data: Reliability Study

BACKGROUND

There is substantial evidence exploring the reliability of running distance self-reporting and GPS wearable technology, but there are currently no studies investigating the reliability of participant self-reporting in comparison to GPS wearable technology. There is also a critical sports science and medical research gap due to a paucity of reliability studies assessing self-reported running pace.

OBJECTIVE

The purpose of this study was to assess the reliability of weekly self-reported running distance and pace compared to a commercial GPS fitness watch, stratified by sex and age. These data will give clinicians and sports researchers insights into the reliability of runners' self-reported pace, which may improve training designs and rehabilitation prescriptions.

METHODS

A prospective study of recreational runners was performed. Weekly running distance and average running pace were captured through self-report and a fitness watch. Baseline characteristics collected included age and sex. Intraclass correlational coefficients were calculated for weekly running distance and running pace for self-report and watch data. Bland-Altman plots assessed any systemic measurement error. Analyses were then stratified by sex and age.

RESULTS

Younger runners reported improved weekly distance reliability (median 0.93, IQR 0.92-0.94). All ages demonstrated similar running pace reliability. Results exhibited no discernable systematic bias.

CONCLUSIONS

Weekly self-report demonstrated good reliability for running distance and moderate reliability for running pace in comparison to the watch data. Similar reliability was observed for male and female participants. Younger runners demonstrated improved running distance reliability, but all age groups exhibited similar pace reliability. Running pace potentially should be monitored through technological means to increase precision.

Changes in running economy and running technique following 6 months of running with and without wearable-based real-time feedback

BACKGROUND

An increasing number of commercially available wearables provide real-time feedback on running biomechanics with the aim to reduce injury risk or improve performance.

OBJECTIVE

Investigate whether real-time feedback by wearable insoles (ARION) alters running biomechanics and improves running economy more as compared to unsupervised running training. We also explored the correlation between changes in running biomechanics and running economy.

METHODS

Forty recreational runners were randomized to an intervention and control group and performed ~6 months of in-field training with or without wearable-based real-time feedback on running technique and speed. Running economy and running biomechanics were measured in lab conditions without feedback pre and post intervention at four speeds.

RESULTS

Twenty-two individuals (13 control, 9 intervention) completed both tests. Both groups significantly reduced their energetic cost by an average of -6.1% and -7.7% for the control and intervention groups, respectively. The reduction in energy cost did not significantly differ between groups overall (-0.07 ± 0.14 J∙kg∙m-1 , -1.5%, p = 0.63). There were significant changes in spatiotemporal metrics, but their magnitude was minor and did not differ between the groups. There were no significant changes in running kinematics within or between groups. However, alterations in running biomechanics beyond typical session-to-session variation were observed during some in-field sessions for individuals that received real-time feedback.

CONCLUSION

Alterations in running biomechanics as observed during some in-field sessions for individuals receiving wearable-based real-time feedback did not result in significant differences in running economy or running biomechanics when measured in controlled lab conditions without feedback.

Exploring running styles in the field through cadence and duty factor modulation

According to the dual-axis model, running styles can be defined by cadence and duty factor, variables that have been associated with running performance, economy and injury risk. To guide runners in exploring different running styles, effective instructions to modulate cadence and duty factor are needed. Such instructions have been established for treadmill running, but not for overground running, during which speed can be varied. In this study, five participants completed eight field training sessions over a 4-week training period with acoustic instructions to modulate cadence, duty factor, and, in combination, running style. Instructions were provided via audio files. Running data were collected with sports watches. Participants' experiences with guided-exploration training were evaluated with the user experience questionnaire. Data analysis revealed acoustic pacing and verbal instructions to be effective in respectively modulating cadence and duty factor, albeit with co-varying effects on speed and the non-targeted variable (i.e. duty factor or cadence). Combining acoustic pacing and verbal instructions mitigated these co-varying effects considerably, allowing for running-style modulations in intended directions (particularly towards the styles with increased cadence and increased duty factor). User experience of this form of guided-exploration training was overall positive, but could be improved in terms of autonomy (dependability). In conclusion, combining acoustic pacing and verbal instructions for running-style modulation is effective in overground running.

The accuracy of commercially available instrumented insoles (ARION) for measuring spatiotemporal running metrics

Spatiotemporal metrics such as step frequency have been associated with running injuries in some studies. Wearables can measure these metrics and provide real-time feedback in-field, but are often not validated. This study assessed the validity of commercially available wireless instrumented insoles (ARION) for quantifying spatiotemporal metrics during level running at different speeds (2.78-5.0 m s-1 ,) and slopes (3° and 6° up/downhill) to an instrumented treadmill. Mean raw, percentage and absolute percentage error, and limits of agreement (LoA) were calculated. Agreement was statistically quantified using four thresholds: excellent, <5%; good, <10%; acceptable, <15%; and poor, >15% error. Excellent agreement (<5% error) was achieved for stride time across all conditions, and for step frequency across all but one condition with good agreement. Contact time and swing time generally showed at least good agreement. The mean difference across all conditions was -0.95% for contact time, 0.11% for stride time, 0.6% for swing time, -0.11% for step frequency, and -0.09% when averaged across all outcomes and conditions. The accuracy at an individual level was generally good to excellent, being <10% for all but two conditions, with these conditions being <15%. Additional experiments among four runners showed that step length could also be measured with an accuracy of 1.76% across different speeds with an updated version of the insoles. These findings suggests that the ARION wearable may not only be useful for large-scale in-field studies investigating group differences, but also to quantify spatiotemporal metrics with generally good to excellent accuracy for individual runners.

Intelligent prediction of lower extremity loadings during badminton lunge footwork in a lab-simulated court

Introduction: Playing badminton has been reported with extensive health benefits, while main injuries were documented in the lower extremity. This study was aimed to investigate and predict the knee- and ankle-joint loadings of athletes who play badminton, with "gold standard" facilities. The axial impact acceleration from wearables would be used to predict joint moments and contact forces during sub-maximal and maximal lunge footwork. Methods: A total of 25 badminton athletes participated in this study, following a previously established protocol of motion capture and musculoskeletal modelling techniques with the integration of a wearable inertial magnetic unit (IMU). We developed a principal component analysis (PCA) statistical model to extract features in the loading parameters and a multivariate partial least square regression (PLSR) machine learning model to correlate easily collected variables, such as the stance time, approaching velocity, and peak accelerations, with knee and ankle loading parameters (moments and contact forces). Results: The key variances of joint loadings were observed from statistical principal component analysis modelling. The promising accuracy of the partial least square regression model using input parameters was observed with a prediction accuracy of 94.52%, while further sensitivity analysis found a single variable from the ankle inertial magnetic unit that could predict an acceptable range (93%) of patterns and magnitudes of the knee and ankle loadings. Conclusion: The attachment of this single inertial magnetic unit sensor could be used to record and predict loading accumulation and distribution, and placement would exhibit less influence on the motions of the lower extremity. The intelligent prediction of loading patterns and accumulation could be integrated to design training and competition schemes in badminton or other court sports in a scientific manner, thus preventing fatigue, reducing loading-accumulation-related injury, and maximizing athletic performance.

Augmented-reality swim goggles accurately and reliably measure swim performance metrics in recreational swimmers

Background

Swimmers commonly access performance metrics such as lap splits, distance, and pacing information between work bouts while they rest. Recently, a new category of tracking devices for swimming was introduced with the FORM Smart Swim Goggles (FORM Goggles). The goggles have a built-in see-through display and are capable of tracking and displaying distance, time splits, stroke, and pace metrics in real time using machine learning and augmented reality through a heads-up display. The purpose of this study was to assess the validity and reliability of the FORM Goggles compared with video analysis for stroke type, pool length count, pool length time, stroke rate, and stroke count in recreational swimmers and triathletes.

Method

A total of 36 participants performed mixed swimming intervals in a 25-m pool across two identical 900-m swim sessions performed at comparable intensities with 1 week interval. The participants wore FORM Goggles during their swims, which detected the following five swim metrics: stroke type, pool length time, pool length count, stroke count, and stroke rate. Four video cameras were positioned on the pool edges to capture ground truth video footage, which was then manually labeled by three trained individuals. Mean (SD) differences between FORM Goggles and ground truth were calculated for the selected metrics for both sessions. The absolute mean difference and mean absolute percentage error were used to assess the differences of the FORM Goggles relative to ground truth. The test-retest reliability of the goggles was assessed using both relative and absolute reliability metrics.

Results

Compared with video analysis, the FORM Goggles identified the correct stroke type at a rate of 99.7% (N = 2,354 pool lengths, p < 0.001), pool length count accuracy of 99.8%, and mean differences (FORM Goggles-ground truth) for pool length time: -0.10 s (1.49); stroke count: -0.63 (1.82); and stroke rate: 0.19 strokes/min (3.23). The test-retest intra-class correlation coefficient (ICC) values between the two test days were 0.793 for pool length time, 0.797 for stroke count, and 0.883 for stroke rate. Overall, for pool length time, the residuals were within ±1.0s for 65.3% of the total pool lengths, for stroke count within ±1 stroke for 62.6% of the total pool lengths, and for stroke rate within ±2 strokes/min for 66.40% of the total pool lengths.

Conclusion

The FORM Goggles were found valid and reliable for the tracking of pool length time, pool length count, stroke count, stroke rate, and stroke type during freestyle, backstroke, and breaststroke swimming in recreational swimmers and triathletes when compared with video analysis. This opens perspectives for receiving real-time information on performance metrics during swimming.

The Effect of Real-Time Tibial Acceleration Feedback on Running Biomechanics During Gait Retraining: A Systematic Review and Meta-Analysis

OBJECTIVES

To explore the immediate and retention effect of real-time tibial acceleration feedback on running biomechanics during gait retraining.

METHODS

Five electronic databases were searched to identify relevant studies published before May 2022. The included studies were evaluated for methodological quality and bias risk, and data were extracted. A meta-analysis was conducted on the primary outcomes, including peak tibial acceleration (PTA) and vertical ground reaction force. Subgroup analysis was performed by gender, feedback criterion, mode, dosage, fading, retention period, and running environment to evaluate the source of heterogeneity. Qualitative analysis was performed to describe other variables.

RESULTS

Fourteen studies (174 participants) were eligible. Meta-analysis showed that real-time tibial acceleration feedback reduced PTA (P < .01, P < .01), vertical impact peak (P = .004, P < .01), vertical average loading rate (P < .01, P < .01), and vertical instantaneous loading rate (P < .01, P < .01) after feedback and during retention period (5 min-12 mo). Subgroup analysis showed that the immediate effect of vertical impact peak was more noticeable with mixed gender (P = .005) and fading feedback (P = .005) conditions, and the retention effect of PTA was more noticeable with high feedback dosage (P < .01) and fading feedback (P < .01) conditions.

CONCLUSIONS

Real-time tibial acceleration feedback can reduce PTA and vertical ground reaction force during gait retraining, and for periods of 5 minutes to 12 months when the feedback is removed.

Sensitiveness of Variables Extracted from a Fitness Smartwatch to Detect Changes in Vertical Impact Loading during Outdoors Running

Accelerometry is becoming a popular method to access human movement in outdoor conditions. Running smartwatches may acquire chest accelerometry through a chest strap, but little is known about whether the data from these chest straps can provide indirect access to changes in vertical impact properties that define rearfoot or forefoot strike. This study assessed whether the data from a fitness smartwatch and chest strap containing a tri-axial accelerometer (FS) is sensible to detect changes in running style. Twenty-eight participants performed 95 m running bouts at ~3 m/s in two conditions: normal running and running while actively reducing impact sounds (silent running). The FS acquired running cadence, ground contact time (GCT), stride length, trunk vertical oscillation (TVO), and heart rate. Moreover, a tri-axial accelerometer attached to the right shank provided peak vertical tibia acceleration (PKACC). The running parameters extracted from the FS and PKACC variables were compared between normal and silent running. Moreover, the association between PKACC and smartwatch running parameters was accessed using Pearson correlations. There was a 13 ± 19% reduction in PKACC (p < 0.005), and a 5 ± 10% increase in TVO from normal to silent running (p < 0.01). Moreover, there were slight reductions (~2 ± 2%) in cadence and GCT when silently running (p < 0.05). However, there were no significant associations between PKACC and the variables extracted from the FS (r < 0.1, p > 0.05). Therefore, our results suggest that biomechanical variables extracted from FS have limited sensitivity to detect changes in running technique. Moreover, the biomechanical variables from the FS cannot be associated with lower limb vertical loading.

Using beat frequency in music to adjust running cadence in recreational runners: A randomized multiple baseline design

Running with music has been shown to acutely change cadence. However, it is unclear if the increased cadence remains long-term when running without music in an in-field situation. The aim of this 12-week study was to investigate the effect of a 4-week music running program on cadence, speed and heartrate during and after the music running program. Seven recreational runners with a cadence of <170 steps per minute were randomly assigned to a baseline and post-intervention period of different durations. During the intervention phase, the participants ran with a musical beat that was 7.5-10% higher than their mean cadence at the start of the study. Cadence, heartrate and running speed were measured twice a week during a 5-kilometer run with a watch, and were analyzed using randomization tests and visual data inspection. Two participants dropped-out due to shortage of time (n = 1) and an acute calf injury (n = 1). Cadence significantly increased during the intervention period (+8.5%), and remained elevated during the post-intervention period (+7.9% (p = .001)) in comparison with the baseline period. Heartrate and running speed did not significantly change during any period. This study among five participants shows that four weeks of running with a musical beat that is 7.5-10% higher than the preferred cadence may be an effective and feasible intervention to increase running cadence. Importantly, the increased cadence occurred without simultaneous increases in running speed and heartrate, hereby potentially reducing mechanical loading without increasing metabolic load.HighlightsRunning with a musical rhythm that is higher than the preferred cadence leads to an increased running cadence, without increasing heartrate and running speed.This cadence remains elevated for at least three to five weeks after the music intervention period.All individuals showed a practically relevant increase in cadence during and after the intervention.

Are Activity Wrist-Worn Devices Accurate for Determining Heart Rate during Intense Exercise?

The market for wrist-worn devices is growing at previously unheard-of speeds. A consequence of their fast commercialization is a lack of adequate studies testing their accuracy on varied populations and pursuits. To provide an understanding of wearable sensors for sports medicine, the present study examined heart rate (HR) measurements of four popular wrist-worn devices, the (Fitbit Charge (FB), Apple Watch (AW), Tomtom runner Cardio (TT), and Samsung G2 (G2)), and compared them with gold standard measurements derived by continuous electrocardiogram examination (ECG). Eight athletes participated in a comparative study undergoing maximal stress testing on a cycle ergometer or a treadmill. We analyzed 1,286 simultaneous HR data pairs between the tested devices and the ECG. The four devices were reasonably accurate at the lowest activity level. However, at higher levels of exercise intensity the FB and G2 tended to underestimate HR values during intense physical effort, while the TT and AW devices were fairly reliable. Our results suggest that HR estimations should be considered cautiously at specific intensities. Indeed, an effective intervention is required to register accurate HR readings at high-intensity levels (above 150 bpm). It is important to consider that even though none of these devices are certified or sold as medical or safety devices, researchers must nonetheless evaluate wrist-worn wearable technology in order to fully understand how HR affects psychological and physical health, especially under conditions of more intense exercise.

Can different training methods reduce the kinematic risk factors of ACL injuries in children?

According to the research, a lack of neuromuscular control is a major cause of non-contact anterior cruciate ligament (ACL) injury during locomotion. This study aimed to determine the influence of various prescriptive and Constrained Led Approach (CLA) training approaches on lower extremity kinematics and stride length in children aged 3-5 years old while walking and running. Thirty-six children with a mean age of 4.79 years were separated into three groups: 1- prescriptive training group (n = 10), 2- CLA training group (n = 11), and 3- Control group (n = 10). The kinematics of the hip, knee and ankle joints in the sagittal plane at the moment of heel contact and toe-off were recorded before and after six weeks of intervention. According to the MANOVA, there was no statistically significant difference between the two training techniques in the joint angles at heel contact and toe-off during walking and running after intervention (p ≥ 0.05). However, there was a significant difference in the kinematic characteristics of walking and running between the training and the control groups (p ≤ 0.05). The two training techniques showed a statistically significant difference in stride length during running (p ≤ 0.05). The results indicated that prescriptive and CLA training are effective at altering the kinematics and distance factors underlying children's walking and running abilities.

PSYCHOLOGICAL QUALITY IN MIDDLE AND LONG-DISTANCE TRAINING

ABSTRACT Introduction: Middle and long-distance running combine endurance and speed, demanding constant speed and minimizing physical losses. Sports fatigue is frequent in competition and the practice of these races. Therefore, middle and long-distance runners are prone to characteristics such as nervousness, negativity, or boredom. Objective: Explore the role of mental health in middle and long-distance runners in track and field events. Methods: Fourteen Chinese middle and long-distance runners were selected. The players undergo a 10-week psychological quality test. A questionnaire survey was conducted before and after completing the 10 weeks of psychological quality education. The data obtained from the experiment were statistically analyzed. The practical teaching of athletes and the form of psychological education were explained and discussed. Results: The psychological quality of stability in the athletes’ movements are reflected inaccurate feedback, the balance of challenging skills, a high sense of control, concentration, and clear purpose. The characteristics of psychological quality were a fusion of awareness of behavior, pleasant experience, loss of self-consciousness, and space-temporal transformation. There were significant differences in the level of stable psychological quality of athletes under different sports levels (P<0.05). Conclusion: Mental quality promotion exercises for middle and long-distance runners can help them to quickly adjust their minds, improving their competitive abilities. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

Quantifying and correcting for speed and stride frequency effects on running mechanics in fatiguing outdoor running

Measuring impact-related quantities in running is of interest to improve the running technique. Many quantities are typically measured in a controlled laboratory setting, even though most runners run in uncontrolled outdoor environments. While monitoring running mechanics in an uncontrolled environment, a decrease in speed or stride frequency can mask fatigue-related changes in running mechanics. Hence, this study aimed to quantify and correct the subject-specific effects of running speed and stride frequency on changes in impact-related running mechanics during a fatiguing outdoor run. Seven runners ran a competitive marathon while peak tibial acceleration and knee angles were measured with inertial measurement units. Running speed was measured through sports watches. Median values over segments of 25 strides throughout the marathon were computed and used to create subject-specific multiple linear regression models. These models predicted peak tibial acceleration, knee angles at initial contact, and maximum stance phase knee flexion based on running speed and stride frequency. Data were corrected for individual speed and stride frequency effects during the marathon. The speed and stride frequency corrected and uncorrected data were divided into ten stages to investigate the effect of marathon stage on mechanical quantities. This study showed that running speed and stride frequency explained, on average, 20%-30% of the variance in peak tibial acceleration, knee angles at initial contact, and maximum stance phase knee angles while running in an uncontrolled setting. Regression coefficients for speed and stride frequency varied strongly between subjects. Speed and stride frequency corrected peak tibial acceleration, and maximum stance phase knee flexion increased throughout the marathon. At the same time, uncorrected maximum stance phase knee angles showed no significant differences between marathon stages due to a decrease in running speed. Hence, subject-specific effects of changes in speed and stride frequency influence the interpretation of running mechanics and are relevant when monitoring, or comparing the gait pattern between runs in uncontrolled environments.

Step-adaptive sound guidance enhances locomotor-respiratory coupling in novice female runners: A proof-of-concept study

Introduction

Many runners struggle to find a rhythm during running. This may be because 20-40% of runners experience unexplained, unpleasant breathlessness at exercise onset. Locomotor-respiratory coupling (LRC), a synchronization phenomenon in which the breath is precisely timed with the steps, may provide metabolic or perceptual benefits to address these limitations. It can also be consciously performed. Hence, we developed a custom smartphone application to provide real-time LRC guidance based on individual step rate.

Methods

Sixteen novice-intermediate female runners completed two control runs outdoors and indoors at a self-selected speed with auditory step rate feedback. Then, the runs were replicated with individualized breath guidance at specific LRC ratios. Hexoskin smart shirts were worn and analyzed with custom algorithms to estimate continuous LRC frequency and phase coupling.

Results

LRC guidance led to a large significant increase in frequency coupling outdoor from 26.3 ± 10.7 (control) to 69.9 ± 20.0 % (LRC) "attached". There were similarly large differences in phase coupling between paired trials, and LRC adherence was stronger for the indoor treadmill runs versus outdoors. There was large inter-individual variability in running pace, preferred LRC ratio, and instruction adherence metrics.

Discussion

Our approach demonstrates how personalized, step-adaptive sound guidance can be used to support this breathing strategy in novice runners. Subsequent investigations should evaluate the skill learning of LRC on a longer time basis to effectively clarify its risks and advantages.

Health-seeking behavior and its associated technology utilization among community-dwelling older adults in Singapore: Qualitative study (Preprint)

BACKGROUND

Understanding older people's health-seeking behavior (HSB) is crucial to uncovering their health needs and priorities, as well as developing appropriate policies to address these needs and avert their disease progression. Technologies play an active role in our daily lives, and they have been incorporated into health activities to support the aging population and facilitate their HSB. However, prior research in HSB has mainly focused on behaviors during illness, and there is limited research on how technologies have been utilized in older people's health-seeking activities.

OBJECTIVE

This study aimed to investigate the HSB and associated technology utilization among the older population, ultimately proposing implications for practice to address their unmet health needs.

METHODS

This paper presented partial data from a larger qualitative study, which has been approved by the Institutional Review Board and employed a phenomenological approach. Semi-structured interviews were conducted between April 2022 and July 2022, either on Zoom or face-to-face. Inclusion criteria included being aged 50 and above, long-term residing in Singapore, and being able to speak English or Mandarin. The interviews were manually transcribed verbatim, and a thematic analysis was performed with the individual as the unit of analysis to understand group phenomena.

RESULTS

Fifteen interviews were conducted to reach thematic saturation. We identified five main consequences of HSB, which were aligned with Poortaghi et al.'s model. Regarding technology utilization in health-seeking, four themes were extracted: 1) the most widely used digital technologies are the mobile health apps and wearable devices with associated wellness programs launched by the government and local companies, and they have the potential to enhance health communication, promote health maintenance, and increase access to health services; 2) information communication technologies and social media, though not primarily designed for health purposes, play a significant role in easing the process of seeking health information and managing symptoms; 3) while the outbreak of the COVID-19 pandemic has resulted in some alterations to older adults' well-being, it has catalyzed the adoption of telehealth as a complement to access healthcare services; and 4) older adults have different considerations when selecting technologies to facilitate their health-seeking and fulfill their health needs. Four archetypes were also proposed based on our findings and the insights gained from our participants' observations in their social networks. These findings led to several implications for practice regarding health communication and promotion, health education, technology design and improvement, telemonitoring service implementation, and solutions to address the needs of each proposed archetype.

CONCLUSIONS

Unlike the commonly held belief that older adults resist technologies and lack technological proficiency, our findings showed that technologies could play a promising role in facilitating older adults' health-seeking. Our findings have implications for the design and implementation of health services and policies.

CLINICALTRIAL

Running-style modulation: Effects of stance-time and flight-time instructions on duty factor and cadence

BACKGROUND

The duty factor (reflecting the ratio of stance to flight time) is an important variable related to running performance, economy, and injury risk. According to the dual-axis model, the duty factor and the cadence are sufficient to describe an individual's running style at a certain speed. To test this model, one should be able to modulate both variables independently. While acoustic pacing is an established method for cadence modulation, no such method is available for duty-factor modulation.

RESEARCH QUESTIONS

Can people modulate their duty factor based on verbal instructions to change either their stance or flight time without changing their cadence? And, if so, which instruction is most effective?

METHODS

Twelve participants ran on an instrumented treadmill and completed four training blocks starting with a baseline trial and ending with a performance trial in which they followed verbal instructions to both increase and decrease their stance and flight time. Acoustic pacing at their preferred cadence was present during the first part of each trial. We calculated the duty factor and cadence for paced and non-paced parts of each trial, assessed the effectiveness of the instructions aimed at changing the duty factor, and examined the effects of instructions and acoustic pacing on cadence using Bayesian statistics.

RESULTS

The duty factor changed in intended directions with verbal instructions to increase and decrease the stance and flight time (18.04 ≤ BF₁₀ ≤ 4954.42), without differences between the instructions or during and after acoustic pacing. The instructions and acoustic pacing did not result in a consistent change in cadence (0.40 ≤ BF₁₀ ≤ 2.59).

SIGNIFICANCE

Runners can change their duty factor through verbal instructions pertaining to stance or flight time, without clear concomitant effects on cadence. Running styles can thus be altered with verbal instructions to change stance or flight time for duty-factor modulation, optionally combined with acoustic pacing to prescribe cadence.

Running-induced fatigue and impact loading in runners: A systematic review and meta-analysis

This systematic review and meta-analysis aimed to synthesise and clarify the effect of running-induced fatigue on impact loading during running. Eight electronic databases were systematically searched until April 2021. Studies that analysed impact loading over the course of a run, in adult runners free of medical conditions were included. Changes in leg stiffness, vertical stiffness, shock attenuation, peak tibial accelerations, peak ground reaction forces (GRF) and loading rates were extracted. Subgroup analyses were conducted depending on whether participants were required to run to exhaustion. Thirty-six studies were included in the review, 25 were included in the meta-analysis. Leg stiffness decreased with running-induced fatigue (SMD -0.31, 95% CI -0.52, -0.08, moderate evidence). Exhaustive and non-exhaustive subgroups were different for peak tibial acceleration (Chi² = 3.79, p = 0.05), with limited evidence from exhaustive subgroups showing an increase in peak tibial acceleration with fatigue. Findings for vertical GRF impact peak and peak braking force were conflicting based on exhaustive and non-exhaustive protocols (Chi² = 3.83, p = 0.05 and Chi² = 5.10, p = 0.02, respectively). Moderate evidence suggests leg stiffness during running decreases with fatigue. Given the non-linear relationship between leg stiffness and running economy, this may have implications for performance.

The Use of Wearable Sensors for Preventing, Assessing, and Informing Recovery from Sport-Related Musculoskeletal Injuries: A Systematic Scoping Review

Wearable technologies are often indicated as tools that can enable the in-field collection of quantitative biomechanical data, unobtrusively, for extended periods of time, and with few spatial limitations. Despite many claims about their potential for impact in the area of injury prevention and management, there seems to be little attention to grounding this potential in biomechanical research linking quantities from wearables to musculoskeletal injuries, and to assessing the readiness of these biomechanical approaches for being implemented in real practice. We performed a systematic scoping review to characterise and critically analyse the state of the art of research using wearable technologies to study musculoskeletal injuries in sport from a biomechanical perspective. A total of 4952 articles were retrieved from the Web of Science, Scopus, and PubMed databases; 165 were included. Multiple study features-such as research design, scope, experimental settings, and applied context-were summarised and assessed. We also proposed an injury-research readiness classification tool to gauge the maturity of biomechanical approaches using wearables. Five main conclusions emerged from this review, which we used as a springboard to propose guidelines and good practices for future research and dissemination in the field.

Review of Real-Time Biomechanical Feedback Systems in Sport and Rehabilitation

Real-time biomechanical feedback (BMF) is a relatively new area of research. The potential of using advanced technology to improve motion skills in sport and accelerate physical rehabilitation has been demonstrated in a number of studies. This paper provides a literature review of BMF systems in sports and rehabilitation. Our motivation was to examine the history of the field to capture its evolution over time, particularly how technologies are used and implemented in BMF systems, and to identify the most recent studies showing novel solutions and remarkable implementations. We searched for papers in three research databases: Scopus, Web of Science, and PubMed. The initial search yielded 1167 unique papers. After a rigorous and challenging exclusion process, 144 papers were eventually included in this report. We focused on papers describing applications and systems that implement a complete real-time feedback loop, which must include the use of sensors, real-time processing, and concurrent feedback. A number of research questions were raised, and the papers were studied and evaluated accordingly. We identified different types of physical activities, sensors, modalities, actuators, communications, settings and end users. A subset of the included papers, showing the most perspectives, was reviewed in depth to highlight and present their innovative research approaches and techniques. Real-time BMF has great potential in many areas. In recent years, sensors have been the main focus of these studies, but new types of processing devices, methods, and algorithms, actuators, and communication technologies and protocols will be explored in more depth in the future. This paper presents a broad insight into the field of BMF.

Heart Rate Measurement Accuracy of Fitbit Charge 4 and Samsung Galaxy Watch Active2: Device Evaluation Study

Background

Fitness trackers and smart watches are frequently used to collect data in longitudinal medical studies. They allow continuous recording in real-life settings, potentially revealing previously uncaptured variabilities of biophysiological parameters and diseases. Adequate device accuracy is a prerequisite for meaningful research.

Objective

This study aims to assess the heart rate recording accuracy in two previously unvalidated devices: Fitbit Charge 4 and Samsung Galaxy Watch Active2.

Methods

Participants performed a study protocol comprising 5 resting and sedentary, 2 low-intensity, and 3 high-intensity exercise phases, lasting an average of 19 minutes 27 seconds. Participants wore two wearables simultaneously during all activities: Fitbit Charge 4 and Samsung Galaxy Watch Active2. Reference heart rate data were recorded using a medically certified Holter electrocardiogram. The data of the reference and evaluated devices were synchronized and compared at 1-second intervals. The mean, mean absolute error, mean absolute percentage error, Lin concordance correlation coefficient, Pearson correlation coefficient, and Bland-Altman plots were analyzed.

Results

A total of 23 healthy adults (mean age 24.2, SD 4.6 years) participated in our study. Overall, and across all activities, the Fitbit Charge 4 slightly underestimated the heart rate, whereas the Samsung Galaxy Watch Active2 overestimated it (−1.66 beats per minute [bpm]/3.84 bpm). The Fitbit Charge 4 achieved a lower mean absolute error during resting and sedentary activities (seated rest: 7.8 vs 9.4; typing: 8.1 vs 11.6; laying down [left]: 7.2 vs 9.4; laying down [back]: 6.0 vs 8.6; and walking slowly: 6.8 vs 7.7 bpm), whereas the Samsung Galaxy Watch Active2 performed better during and after low- and high-intensity activities (standing up: 12.3 vs 9.0; walking fast: 6.1 vs 5.8; stairs: 8.8 vs 6.9; squats: 15.7 vs 6.1; resting: 9.6 vs 5.6 bpm).

Conclusions

Device accuracy varied with activity. Overall, both devices achieved a mean absolute percentage error of just <10%. Thus, they were considered to produce valid results based on the limits established by previous work in the field. Neither device reached sufficient accuracy during seated rest or keyboard typing. Thus, both devices may be eligible for use in respective studies; however, researchers should consider their individual study requirements.

Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis

Inertial measurement units (IMUs) can be used to monitor running biomechanics in real-world settings, but IMUs are often used within a laboratory. The purpose of this scoping review was to describe how IMUs are used to record running biomechanics in both laboratory and real-world conditions. We included peer-reviewed journal articles that used IMUs to assess gait quality during running. We extracted data on running conditions (indoor/outdoor, surface, speed, and distance), device type and location, metrics, participants, and purpose and study design. A total of 231 studies were included. Most (72%) studies were conducted indoors; and in 67% of all studies, the analyzed distance was only one step or stride or <200 m. The most common device type and location combination was a triaxial accelerometer on the shank (18% of device and location combinations). The most common analyzed metric was vertical/axial magnitude, which was reported in 64% of all studies. Most studies (56%) included recreational runners. For the past 20 years, studies using IMUs to record running biomechanics have mainly been conducted indoors, on a treadmill, at prescribed speeds, and over small distances. We suggest that future studies should move out of the lab to less controlled and more real-world environments.

Assessment of Peak Oxygen Uptake with a Smartwatch and its Usefulness for Training of Runners

Peak oxygen uptake (˙VO _2peak ) is an important factor contributing to running performance. Wearable technology may allow the assessment of ˙VO _2peak more frequently and on a larger scale. We aim to i) validate the ˙VO _2peak assessed by a smartwatch (Garmin Forerunner 245), and ii) discuss how this parameter may assist to evaluate and guide training procedures. A total of 23 runners (12 female, 11 male; ˙VO _2peak : 48.6±6.8 ml∙min ⁻¹ ∙kg ⁻¹ ) visited the laboratory twice to determine their ˙VO _2peak during a treadmill ramp test. Between laboratory visits, participants wore a smartwatch and performed three outdoor runs to obtain ˙VO _2peak values provided by the smartwatch. The ˙VO _2peak obtained by the criterion measure ranged from 38 to 61 ml∙min ⁻¹ ∙kg ⁻¹ . The mean absolute percentage error (MAPE) between the smartwatch and the criterion ˙VO _2peak was 5.7%. The criterion measure revealed a coefficient of variation of 4.0% over the VO2peak range from 38–61 ml∙min ⁻¹ ∙kg ⁻¹ . MAPE between the smartwatch and criterion measure was 7.1, 4.1 and −6.2% when analyzing ˙VO _2peak ranging from 39–45 ml∙min ⁻¹ ∙kg ⁻¹ , 45–55 ml∙min ⁻¹ ∙kg ⁻¹ or 55–61 ml∙min ⁻¹ ∙kg ⁻¹ , respectively.

Wearables for Biomechanical Performance Optimization and Risk Assessment in Industrial and Sports Applications

Wearable technologies are emerging as a useful tool with many different applications. While these devices are worn on the human body and can capture numerous data types, this literature review focuses specifically on wearable use for performance enhancement and risk assessment in industrial- and sports-related biomechanical applications. Wearable devices such as exoskeletons, inertial measurement units (IMUs), force sensors, and surface electromyography (EMG) were identified as key technologies that can be used to aid health and safety professionals, ergonomists, and human factors practitioners improve user performance and monitor risk. IMU-based solutions were the most used wearable types in both sectors. Industry largely used biomechanical wearables to assess tasks and risks wholistically, which sports often considered the individual components of movement and performance. Availability, cost, and adoption remain common limitation issues across both sports and industrial applications.

Reliability and Validity of Running Cadence and Stance Time Derived from Instrumented Wireless Earbuds

Instrumented earbuds equipped with accelerometers were developed in response to limitations of currently used running wearables regarding sensor location and feedback delivery. The aim of this study was to assess test-retest reliability, face validity and concurrent validity for cadence and stance time in running. Participants wore an instrumented earbud (new method) while running on a treadmill with embedded force-plates (well-established method). They ran at a range of running speeds and performed several instructed head movements while running at a comfortable speed. Cadence and stance time were derived from raw earbud and force-plate data and compared within and between both methods using t-tests, ICC and Bland-Altman analysis. Test-retest reliability was good-to-excellent for both methods. Face validity was demonstrated for both methods, with cadence and stance time varying with speed in to-be-expected directions. Between-methods agreement for cadence was excellent for all speeds and instructed head movements. For stance time, agreement was good-to-excellent for all conditions, except while running at 13 km/h and shaking the head. Overall, the measurement of cadence and stance time using an accelerometer embedded in a wireless earbud showed good test-retest reliability, face validity and concurrent validity, indicating that instrumented earbuds may provide a promising alternative to currently used wearable systems.

Effects of acoustically paced cadence modulation on impact forces in running

BACKGROUND

Increasing cadence in running has been advocated as a means to improve performance and reduce impact forces. Although acoustic pacing can be used for this purpose, it might by itself lead to an increased impact force, which would counteract the decrease in impact force that is being pursued by increasing the cadence with acoustic pacing and thus have a counterproductive effect.

RESEARCH QUESTION

What are the effects of acoustic pacing and cadence on peak impact force and loading rate during running?

METHODS

Unpublished data from a previous study, in which 16 participants ran on an instrumented treadmill with various forms of acoustic pacing, were analyzed to address the research question. Peak impact force and loading rate while running with and without pacing, at three different cadences were extracted from the ground reaction force data and compared statistically between these two main conditions. In addition, we compared step-based and stride-based pacing, and paced and unpaced steps within stride-based pacing conditions.

RESULTS

As expected, increasing the cadence was accompanied by a significant reduction in peak impact force and instantaneous vertical loading rate, whereas acoustic pacing had no significant effect on the impact forces compared to unpaced running with similar cadence, both before and after pacing. There were also no significant differences in this regard between step-based and stride-based pacing.

SIGNIFICANCE

Acoustic pacing does not adversely affect impact force when used to increase cadence in running with the aim of reducing the impact force and can thus be used for this purpose without introducing a counterproductive effect.

Relationship between Biological, Training, and Physical Fitness Variables in the Expression of Performance in Non-Professional Runners

Sports performance is a multifactorial trait that can be associated with individual and environmental characteristics. In this study, the sample comprised 35 male runners, enrolled in the "InTrack" project. Information regarding variables related to runners' training was obtained via an online questionnaire, while anthropometric and body composition variables, as well as physical fitness components (muscular power, isometric strength, local muscular endurance, agility, and aerobic capacity) were measured, and a global physical fitness score (based on physical fitness components measured) was computed. The Weltman test (3200 m) was used to estimate runners' pace and their stride frequency. Linear regression was used, taking the running pace as dependent variable. The final model, comprising biological, physical fitness, spatiotemporal, and training variables, explained 86% of the running performance variance. Muscular power (β = -1.02; 95% CI = (-1.69)-(-0.35)), abdominal muscle endurance (β = -4.81; 95% CI = (-7.52)-(-2.10)), isometric strength (β = -422.95; 95% CI = (-689.65)-(-156.25)), global physical fitness (β = 27.14; 95% CI = 9.52-45.03), and stride frequency (β = -2.99; 95% CI = (-4.29)-(-1.69)) were significantly associated with performance, meaning that better results in tests and increasing the stride frequency leads to better performance. Individual characteristics and physical fitness components were demonstrated to be significant predictors for running performance.

Misuse of the term 'load' in sport and exercise science

Despite the International System of Units (SI), as well as several publications guiding researchers on correct use of terminology, there continues to be widespread misuse of mechanical terms such as 'work' in sport and exercise science. A growing concern is the misuse of the term 'load'. Terms such as 'training load' and 'PlayerLoad' are popular in sport and exercise science vernacular. However, a 'load' is a mechanical variable which, when used appropriately, describes a force and therefore should be accompanied with the SI-derived unit of the newton (N). It is tempting to accept popular terms and nomenclature as scientific. However, scientists are obliged to abide by the SI and must pay close attention to scientific constructs. This communication presents a critical reflection on the use of the term 'load' in sport and exercise science. We present ways in which the use of this term breaches principles of science and provide practical solutions for ongoing use in research and practice.

The Epidemiology, Risk Factors, and Nonsurgical Treatment of Injuries Related to Endurance Running

ABSTRACT

Running is a popular form of exercise that is easily accessible to various populations; endurance running, defined as distances beyond 5 km, continues to grow within the sport. Endurance running-related injuries are common in the lower extremities and are primarily overuse related. A multitude of risk factors for injury exist, including extrinsic factors, such as running distance and frequency, and intrinsic factors, such as biomechanics and nutrition status. Training and rehabilitation techniques vary with a general focus on strengthening and gradual increase in activity, but evidence is mixed, and it is difficult to generalize programs across different running populations. Management of specific running groups, including youth runners, is an area in which additional research is needed. New treatments, such as orthobiologics and wearable technology, have promising potential to optimize performance and recovery and minimize injury. However, they need to be further evaluated with high-quality studies.

Use of wearable sensors to identify biomechanical alterations in runners with Exercise-Related lower leg pain

Exercise-related lower leg pain (ERLLP) is one of the most prevalent running-related injuries, however little is known about injured runners' mechanics during outdoor running. Establishing biomechanical alterations among ERLLP runners would help guide clinical interventions. Therefore, we sought to a) identify defining biomechanical features among ERLLP runners compared to healthy runners during outdoor running, and b) identify biomechanical thresholds to generate objective gait-training recommendations. Thirty-two ERLLP (13 M, age: 21 ± 5 years, BMI: 22.69 ± 2.25 kg/m²) and 32 healthy runners (13 M, age: 23 ± 6 years, BMI: 22.33 ± 3.20 kg/m²) were assessed using wearable sensors during one week of typical outdoor training. Step-by-step data were extracted to assess kinetic, kinematic, and spatiotemporal measures. Preliminary feature extraction analyses were conducted to determine key biomechanical differences between healthy and ERLLP groups. Analyses of covariance (ANCOVA) and variability assessments were used compare groups on the identified features. Participants were split into 3 pace bands, and mean differences across groups were calculated to establish biomechanical thresholds. Contact time was the key differentiating feature for ERRLP runners. ANCOVA assessments reflected that the ERLLP group had increased contact time (Mean Difference [95% Confidence Interval] = 8 ms [6.9,9.1], p < .001), and approximate entropy analyses reflected greater contact time variability. Contact time differences were dependent upon running pace, with larger between-group differences being exhibited at faster paces. In all, ERLLP runners demonstrated longer contact time than healthy runners during outdoor training. Clinicians should consider contact time when assessing and treating these ERLLP runner patients.

How Are Sports-Trackers Used by Runners? Running-Related Data, Personal Goals, and Self-Tracking in Running

The purpose of this research is to explore the roles that sports trackers and running-related data play in runners’ personal goal achievement. A two-week diary study and semi-structured interviews were conducted with 22 runners to explore how runners engage with their running-related data to set and achieve their running goals. We found that participants pursued and transitioned between different running goals as their needs, abilities, and surrounding environment changed. We also found multiple motivations that shaped the use of sports trackers. We identified two main categories in runners’ motivations for using trackers and data to achieve their goals. These categories were (i) documenting and tracking in running, and (ii) supporting goal-oriented reflections and actions, with various reasons for use while preparing for and during running. This study provides insights into the psychological effects of running-related data and signals practical implications for runners and developers of tracking technology.

Discriminant Analysis of Anthropometric and Training Variables among Runners of Different Competitive Levels

The purpose of this study was to investigate the multivariate profile of different types of Brazilian runners and to identify the discriminant pattern of the distinct types of runners, as a runners' ability to self-classify well. The sample comprised 1235 Brazilian runners of both sexes (492 women; 743 men), with a mean age of 37.94 ± 9.46 years. Individual characteristics were obtained through an online questionnaire: Sex, age, body height (m) and body mass (kg), socioeconomic status, and training information (i.e., self-classification, practice time, practice motivation, running pace, frequency and training volume/week). Multivariate analysis of variance was conducted by sex and the discriminant analysis was used to identify which among running pace, practice time, body mass index and volume/training could differentiate groups such as "professional athletes", "amateur athletes" and "recreational athletes". For both sexes, running pace was the variable that better discriminated the groups, followed by BMI and volume/week. The practice time is not a good indicator to differentiate runner's types. In both sexes, semi-professional runners were those that better self-classify themselves, with amateur runners presenting the highest classification error. This information can be used to guide the long-term training, athlete's selection programs, and to identify the strengths and weaknesses of athletes.

Wearable Technology May Assist in Retraining Foot Strike Patterns in Previously Injured Military Service Members: A Prospective Case Series

A rearfoot strike (RFS) pattern with increased average vertical loading rates (AVLR) while running has been associated with injury. This study evaluated the ability of an instrumented sock, which provides real-time foot strike and cadence audio biofeedback, to transition previously injured military service members from a RFS to a non-rearfoot strike (NRFS) running pattern. Nineteen RFS runners (10 males, 9 females) were instructed to wear the instrumented socks to facilitate a change in foot strike while completing an independent walk-to-run progression and lower extremity exercise program. Kinetic data were collected during treadmill running while foot strike was determined using video analysis at initial (T1), post-intervention (T2), and follow-up (T3) data collections. Nearly all runners (18/19) transitioned to a NRFS pattern following intervention (8 ± 2.4 weeks after the initial visit). Most participants (16/18) maintained the transition at follow-up (5 ± 0.8 weeks after the post-intervention visit). AVLR of the involved and uninvolved limb decreased 29% from initial [54.7 ± 13.2 bodyweights per sec (BW/s) and 55.1 ± 12.7 BW/s] to post-intervention (38.7 ± 10.1 BW/s and 38.9 ± 10.0 BW/s), respectively. This effect persisted 5-weeks later at follow-up, representing an overall 30% reduction on the involved limb and 24% reduction on the uninvolved limb. Cadence increased from the initial to the post-intervention time-point (p = 0.045); however, this effect did not persist at follow-up (p = 0.08). With technology provided feedback from instrumented socks, approximately 90% of participants transitioned to a NRFS pattern, decreased AVLR, reduced stance time and maintained these running adaptations 5-weeks later.

Can an inertial measurement unit (IMU) in combination with machine learning measure fast bowling speed and perceived intensity in cricket?

This study examined whether an inertial measurement unit (IMU), in combination with machine learning, could accurately predict two indirect measures of bowling intensity through ball release speed (BRS) and perceived intensity zone (PIZ). One IMU was attached to the thoracic back of 44 fast bowlers. Each participant bowled 36 deliveries at two different PIZ zones (Zone 1 = 24 deliveries at 70% to 85% of maximum perceived bowling effort; Zone 2 = 12 deliveries at 100% of maximum perceived bowling effort) in a random order. IMU data (sampling rate = 250 Hz) were downsampled to 125 Hz, 50 Hz, and 25 Hz to determine if model accuracy was affected by the sampling frequency. Data were analysed using four machine learning models. A two-way repeated-measures ANOVA was used to compare the mean absolute error (MAE) and accuracy scores (separately) across the four models and four sampling frequencies. Gradient boosting models were shown to be the most consistent at measuring BRS (MAE = 3.61 km/h) and PIZ (F-score = 88%) across all sampling frequencies. This method could be used to measure BRS and PIZ which may contribute to a better understanding of overall bowling load which may help to reduce injuries.

Effects of Wearable Devices with Biofeedback on Biomechanical Performance of Running-A Systematic Review

This present review includes a systematic search for peer-reviewed articles published between March 2009 and March 2020 that evaluated the effects of wearable devices with biofeedback on the biomechanics of running. The included articles did not focus on physiological and metabolic metrics. Articles with patients, animals, orthoses, exoskeletons and virtual reality were not included. Following the PRISMA guidelines, 417 articles were first identified, and nineteen were selected following the removal of duplicates and articles which did not meet the inclusion criteria. Most reviewed articles reported a significant reduction in positive peak acceleration, which was found to be related to tibial stress fractures in running. Some previous studies provided biofeedback aiming to increase stride frequencies. They produced some positive effects on running, as they reduced vertical load in knee and ankle joints and vertical displacement of the body and increased knee flexion. Some other parameters, including contact ground time and speed, were fed back by wearable devices for running. Such devices reduced running time and increased swing phase time. This article reviews challenges in this area and suggests future studies can evaluate the long-term effects in running biomechanics produced by wearable devices with biofeedback.

A Random Forest Machine Learning Framework to Reduce Running Injuries in Young Triathletes

Background: The running segment of a triathlon produces 70% of the lower limb injuries. Previous research has shown a clear association between kinematic patterns and specific injuries during running. Methods: After completing a seven-month gait retraining program, a questionnaire was used to assess 19 triathletes for the incidence of injuries. They were also biomechanically analyzed at the beginning and end of the program while running at a speed of 90% of their maximum aerobic speed (MAS) using surface sensor dynamic electromyography and kinematic analysis. We used classification tree (random forest) techniques from the field of artificial intelligence to identify linear and non-linear relationships between different biomechanical patterns and injuries to identify which styles best prevent injuries. Results: Fewer injuries occurred after completing the program, with athletes showing less pelvic fall and greater activation in gluteus medius during the first phase of the float phase, with increased trunk extension, knee flexion, and decreased ankle dorsiflexion during the initial contact with the ground. Conclusions: The triathletes who had suffered the most injuries ran with increased pelvic drop and less activation in gluteus medius during the first phase of the float phase. Contralateral pelvic drop seems to be an important variable in the incidence of injuries in young triathletes.