Accuracy of human motion capture systems for sport applications; state-of-the-art review

Assessing and Enhancing Movement Quality Using Wearables and Consumer Technologies: Thematic Analysis of Expert Perspectives

BACKGROUND

Improvements in movement quality (ie, how well an individual moves) facilitate increases in movement quantity, subsequently improving general health and quality of life. Wearable technology offers a convenient, affordable means of measuring and assessing movement quality for the general population, while technology more broadly can provide constructive feedback through various modalities. Considering the perspectives of professionals involved in the development and implementation of technology helps translate user needs into effective strategies for the optimal application of consumer technologies to enhance movement quality.

OBJECTIVE

This study aimed to obtain the opinions of wearable technology experts regarding the use of wearable devices to measure movement quality and provide feedback. A secondary objective was to determine potential strategies for integrating preferred assessment and feedback characteristics into a technology-based movement quality intervention for the general, recreationally active population.

METHODS

Semistructured interviews were conducted with 12 participants (age: mean 42, SD 9 years; 5 males) between August and September 2022 using a predetermined interview schedule. Participants were categorized based on their professional roles: commercial (n=4) and research and development (R&D; n=8). All participants had experience in the development or application of wearable technology for sports, exercise, and wellness. The verbatim interview transcripts were analyzed using reflexive thematic analysis in QSR NVivo (release 1.7), resulting in the identification of overarching themes and subthemes.

RESULTS

Three main themes were generated as follows: (1) "Grab and Go," (2) "Adjust and Adapt," and (3) "Visualize and Feedback." Participants emphasized the importance of convenience to enhance user engagement when using wearables to collect movement data. However, it was suggested that users would tolerate minor inconveniences if the benefits were perceived as valuable. Simple, easily interpretable feedback was recommended to accommodate diverse audiences and aid understanding of their movement quality, while avoiding excessive detail was advised to prevent overload, which could deter users. Adaptability was endorsed to accommodate progressions in user movement quality, and customizable systems were advocated to offer variety, thereby increasing user interest and engagement. The findings indicate that visual feedback representative of the user (ie, an avatar) should be used, supplemented with concise text or audible instructions to form a comprehensive, multimodal feedback system.

CONCLUSIONS

The study provides insights from wearable technology experts on the use of consumer technologies for enhancing movement quality. The findings recommend the prioritization of user convenience and simplistic, multimodal feedback centered around visualizations, and an adaptable system suitable for a diverse audience. Emphasizing individualized feedback and user-centric design, this study provides valuable findings around the use of wearables and other consumer technologies to enhance movement quality among the general population. These findings, in conjunction with those of future research into user perspectives, should be applied in practical settings to evaluate their effectiveness in enhancing movement quality.

Validity of Valor Inertial Measurement Unit for Upper and Lower Extremity Joint Angles

Inertial measurement units (IMU) are increasingly utilized to capture biomechanical measures such as joint kinematics outside traditional biomechanics laboratories. These wearable sensors have been proven to help clinicians and engineers monitor rehabilitation progress, improve prosthesis development, and record human performance in a variety of settings. The Valor IMU aims to offer a portable motion capture alternative to provide reliable and accurate joint kinematics when compared to industry gold standard optical motion capture cameras. However, IMUs can have disturbances in their measurements caused by magnetic fields, drift, and inappropriate calibration routines. Therefore, the purpose of this investigation is to validate the joint angles captured by the Valor IMU in comparison to an optical motion capture system across a variety of movements. Our findings showed mean absolute differences between Valor IMU and Vicon motion capture across all subjects' joint angles. The tasks ranged from 1.81 degrees to 17.46 degrees, the root mean squared errors ranged from 1.89 degrees to 16.62 degrees, and interclass correlation coefficient agreements ranged from 0.57 to 0.99. The results in the current paper further promote the usage of the IMU system outside traditional biomechanical laboratories. Future examinations of this IMU should include smaller, modular IMUs with non-slip Velcro bands and further validation regarding transverse plane joint kinematics such as joint internal/external rotations.

Is There a Pathologic Running Motion Associated with Running-Related Injuries? A Methodological Study Using a Motion Analysis System Without Sensors

(1) Background and objectives: Running-related injuries (RRIs) are commonly attributed to improper running posture and overuse. This study aims to analyze the running motions of individuals with and without RRIs using a sensor-free method, which offers a user-friendly and straightforward approach. (2) Materials and Methods: A total of 155 runners were divided into two groups: the normal runner group (runners who had never been injured, n = 50) and the RRI group (runners who had experience at least one injury while running, n = 105). The forward head posture (FHP), trunk lean, hip rotation, horizontal movement of the center of gravity (COG), vertical movement of the COG, pelvic rotation, hip hike, and type of strike were measured for posture analysis. (3) Results: We found that the left-right balance of the pelvis and the spinal posture during running were associated with RRIs. The difference in hip hike and FHP emerged as key predictors of running-related musculoskeletal injury occurrence from our logistic regression analysis. (4) Conclusions: Identifying pathological movements in runners through running motion analysis without the use of sensors can be instrumental in the prevention and treatment of RRIs.

Shoulder Motion Overestimated by Mallet Scores

BACKGROUND

Brachial plexus birth injuries (BPBI) occur in up 0.4 to 4.6 per 1000 live births. Weakness about the shoulder and development of glenohumeral joint contractures are common sequalae of BPBI. Shoulder function in children with BPBI is frequently assessed using the modified Mallet classification to evaluate upper extremity motion deficits. The purpose of this study was to assess the accuracy of the abduction, external rotation, and hand-to-mouth Mallet classification scores in children with BPBI using motion capture.

METHODS

A retrospective study of 107 children with BPBI who underwent motion capture assessment and Mallet scores on the same date were reviewed. Motion capture measurements were used to calculate humerothoracic elevation and external rotation joint angles in the abduction/hand-to-mouth and external rotation positions, respectively. The humerothoracic joint angles were converted to the corresponding Mallet scores. Discrepancies between the Mallet scores determined by clinicians and those determined by motion capture were assessed.

RESULTS

For abduction, 24.3% of Mallet scores were misclassified during clinical examination. Of the misclassified scores, 22 were overestimated by 1 point and 4 were underestimated by 1 point compared with motion capture. For external rotation, 72.9% of Mallet scores were misclassified during clinical examination. Only 5 patients had an HT elevation that was less than 40 degrees, with 4 of them (80%) having a Mallet hand-to-mouth score of 4. There were no differences in proportion of patients with HT elevation less than 40 degrees who had a Mallet score of 4 or a Mallet score less than 4.

CONCLUSIONS

There was better agreement in global abduction Mallet scores compared with external rotation and hand-to-mouth Mallet scores. This difference was likely due to the complex compensatory strategies that patients employ while performing external rotation and hand-to-mouth positions. The inaccuracy of the clinically determined Mallet scores is alarming given that they are frequently utilized to assist with surgical indications and are commonly used as outcome measures.

LEVEL OF EVIDENCE

Level IV Case series.

Large-Scale Indoor Camera Positioning Using Fiducial Markers

Estimating the pose of a large set of fixed indoor cameras is a requirement for certain applications in augmented reality, autonomous navigation, video surveillance, and logistics. However, accurately mapping the positions of these cameras remains an unsolved problem. While providing partial solutions, existing alternatives are limited by their dependence on distinct environmental features, the requirement for large overlapping camera views, and specific conditions. This paper introduces a novel approach to estimating the pose of a large set of cameras using a small subset of fiducial markers printed on regular pieces of paper. By placing the markers in areas visible to multiple cameras, we can obtain an initial estimation of the pair-wise spatial relationship between them. The markers can be moved throughout the environment to obtain the relationship between all cameras, thus creating a graph connecting all cameras. In the final step, our method performs a full optimization, minimizing the reprojection errors of the observed markers and enforcing physical constraints, such as camera and marker coplanarity and control points. We validated our approach using novel artificial and real datasets with varying levels of complexity. Our experiments demonstrated superior performance over existing state-of-the-art techniques and increased effectiveness in real-world applications. Accompanying this paper, we provide the research community with access to our code, tutorials, and an application framework to support the deployment of our methodology.

Influence of angular position on radar gun peak cricket ball speed measurements

The purpose of this study was to determine the agreement in peak ball speed measured using a radar gun and motion capture system then examine the influence of angular position. Peak ball speed was recorded with the radar gun in-line with the ball trajectory (0° offset) and at 5° offsets up to 35°. Agreement between devices was calculated at 0° and for grouped offset bins (0-5°, 10-15°, 20-25°, and 30-35°). At 0°, a strong correlation (r = 0.99) and intraclass correlation coefficient (.984) were observed with a systematic overestimation by the radar gun (1.7 ± 0.8 m/s). The residual speed between devices at the 30-35° offset was significantly different to both 0-5° (p < .001) and 10-15° (p < .001) offsets. The radar gun consistently overestimated peak ball speed up to a ~20° offset and thus can be positioned out of the line-of-throw to avoid obstructions.

Validation of Step Detection and Distance Calculation Algorithms for Soccer Performance Monitoring

This study focused on developing and evaluating a gyroscope-based step counter algorithm using inertial measurement unit (IMU) readings for precise athletic performance monitoring in soccer. The research aimed to provide reliable step detection and distance estimation tailored to soccer-specific movements, including various running speeds and directional changes. Real-time algorithms utilizing shank angular data from gyroscopes were created. Experiments were conducted on a specially designed soccer-specific testing circuit performed by 15 athletes, simulating a range of locomotion activities such as walking, jogging, and high-intensity actions. The algorithm outcome was compared with manually tagged data from a high-quality video camera-based system for validation, by assessing the agreement between the paired values using limits of agreement, concordance correlation coefficient, and further metrics. Results returned a step detection accuracy of 95.8% and a distance estimation Root Mean Square Error (RMSE) of 17.6 m over about 202 m of track. A sub-sample (N = 6) also wore two pairs of devices concurrently to evaluate inter-unit reliability. The performance analysis suggested that the algorithm was effective and reliable in tracking diverse soccer-specific movements. The proposed algorithm offered a robust and efficient solution for tracking step count and distance covered in soccer, particularly beneficial in indoor environments where global navigation satellite systems are not feasible. This advancement in sports technology widens the spectrum of tools for coaches and athletes in monitoring soccer performance.

Implementation of a Long Short-Term Memory Neural Network-Based Algorithm for Dynamic Obstacle Avoidance

Autonomous mobile robots are essential to the industry, and human-robot interactions are becoming more common nowadays. These interactions require that the robots navigate scenarios with static and dynamic obstacles in a safely manner, avoiding collisions. This paper presents a physical implementation of a method for dynamic obstacle avoidance using a long short-term memory (LSTM) neural network that obtains information from the mobile robot's LiDAR for it to be capable of navigating through scenarios with static and dynamic obstacles while avoiding collisions and reaching its goal. The model is implemented using a TurtleBot3 mobile robot within an OptiTrack motion capture (MoCap) system for obtaining its position at any given time. The user operates the robot through these scenarios, recording its LiDAR readings, target point, position inside the MoCap system, and its linear and angular velocities, all of which serve as the input for the LSTM network. The model is trained on data from multiple user-operated trajectories across five different scenarios, outputting the linear and angular velocities for the mobile robot. Physical experiments prove that the model is successful in allowing the mobile robot to reach the target point in each scenario while avoiding the dynamic obstacle, with a validation accuracy of 98.02%.

Motion Capture Technology in Sports Scenarios: A Survey

Motion capture technology plays a crucial role in optimizing athletes' skills, techniques, and strategies by providing detailed feedback on motion data. This article presents a comprehensive survey aimed at guiding researchers in selecting the most suitable motion capture technology for sports science investigations. By comparing and analyzing the characters and applications of different motion capture technologies in sports scenarios, it is observed that cinematography motion capture technology remains the gold standard in biomechanical analysis and continues to dominate sports research applications. Wearable sensor-based motion capture technology has gained significant traction in specialized areas such as winter sports, owing to its reliable system performance. Computer vision-based motion capture technology has made significant advancements in recognition accuracy and system reliability, enabling its application in various sports scenarios, from single-person technique analysis to multi-person tactical analysis. Moreover, the emerging field of multimodal motion capture technology, which harmonizes data from various sources with the integration of artificial intelligence, has proven to be a robust research method for complex scenarios. A comprehensive review of the literature from the past 10 years underscores the increasing significance of motion capture technology in sports, with a notable shift from laboratory research to practical training applications on sports fields. Future developments in this field should prioritize research and technological advancements that cater to practical sports scenarios, addressing challenges such as occlusion, outdoor capture, and real-time feedback.

An Investigation of Running Kinematics with Recovered Anterior Cruciate Ligament Reconstruction on a Treadmill and In-Field Using Inertial Measurement Units: A Preliminary Study

Anterior cruciate ligament reconstruction (ACLR) may affect movement even years after surgery. The purpose of this study was to determine possible interlimb asymmetries due to ACLR when running on a treadmill and in field conditions, with the aim of contributing to the establishment of objective movement assessment in real-world settings; moreover, we aimed to gain knowledge on recovered ACLR as a biomechanical risk factor. Eight subjects with a history of unilateral ACLR 5.4 ± 2.8 years after surgery and eight healthy subjects ran 1 km on a treadmill and 1 km on a concrete track. The ground contact time and triaxial peak tibial accelerations were recorded using inertial measurement units. Interlimb differences within subjects were tested and compared between conditions. There were no significant differences between limbs in the ACLR subjects or in healthy runners for any of the chosen parameters on both running surfaces. However, peak tibial accelerations were higher during field running (p-values < 0.01; Cohen's d effect sizes > 0.8), independent of health status. To minimize limb loading due to higher impacts during field running, this should be considered when choosing a running surface, especially in rehabilitation or when running with a minor injury or health issues.

Enhancing volleyball training: empowering athletes and coaches through advanced sensing and analysis

Modern sensing technologies and data analysis methods usher in a new era for sports training and practice. Hidden insights can be uncovered and interactive training environments can be created by means of data analysis. We present a system to support volleyball training which makes use of Inertial Measurement Units, a pressure sensitive display floor, and machine learning techniques to automatically detect relevant behaviours and provides the user with the appropriate information. While working with trainers and amateur athletes, we also explore potential applications that are driven by automatic action recognition, that contribute various requirements to the platform. The first application is an automatic video-tagging protocol that marks key events (captured on video) based on the automatic recognition of volleyball-specific actions with an unweighted average recall of 78.71% in the 10-fold cross-validation setting with convolution neural network and 73.84% in leave-one-subject-out cross-validation setting with active data representation method using wearable sensors, as an exemplification of how dashboard and retrieval systems would work with the platform. In the context of action recognition, we have evaluated statistical functions and their transformation using active data representation besides raw signal of IMUs sensor. The second application is the "bump-set-spike" trainer, which uses automatic action recognition to provide real-time feedback about performance to steer player behaviour in volleyball, as an example of rich learning environments enabled by live action detection. In addition to describing these applications, we detail the system components and architecture and discuss the implications that our system might have for sports in general and for volleyball in particular.

Biomechanical Assessment Methods Used in Chronic Stroke: A Scoping Review of Non-Linear Approaches

Non-linear and dynamic systems analysis of human movement has recently become increasingly widespread with the intention of better reflecting how complexity affects the adaptability of motor systems, especially after a stroke. The main objective of this scoping review was to summarize the non-linear measures used in the analysis of kinetic, kinematic, and EMG data of human movement after stroke. PRISMA-ScR guidelines were followed, establishing the eligibility criteria, the population, the concept, and the contextual framework. The examined studies were published between 1 January 2013 and 12 April 2023, in English or Portuguese, and were indexed in the databases selected for this research: PubMed®, Web of Science®, Institute of Electrical and Electronics Engineers®, Science Direct® and Google Scholar®. In total, 14 of the 763 articles met the inclusion criteria. The non-linear measures identified included entropy (n = 11), fractal analysis (n = 1), the short-term local divergence exponent (n = 1), the maximum Floquet multiplier (n = 1), and the Lyapunov exponent (n = 1). These studies focused on different motor tasks: reaching to grasp (n = 2), reaching to point (n = 1), arm tracking (n = 2), elbow flexion (n = 5), elbow extension (n = 1), wrist and finger extension upward (lifting) (n = 1), knee extension (n = 1), and walking (n = 4). When studying the complexity of human movement in chronic post-stroke adults, entropy measures, particularly sample entropy, were preferred. Kinematic assessment was mainly performed using motion capture systems, with a focus on joint angles of the upper limbs.

Reliability of Markerless Motion Capture Systems for Assessing Movement Screenings

Background

Movement screenings are commonly used to detect unfavorable movement patterns. Markerless motion capture systems have been developed to track 3-dimensional motion.

Purpose

To determine the reliability of movement screenings assessed using a markerless motion capture system when comparing the results of multiple systems and multiple collection periods.

Study Design

Descriptive laboratory study.

Methods

The inter- and intrarater reliability of a commercially available markerless motion capture system were investigated in 21 recreationally active participants aged between 18 and 22 years. A total of 39 kinematic variables arising from 10 fundamental upper and lower body movements typical of a screening procedure in sports performance were considered. The data were statistically analyzed in terms of relative error via the intraclass correlation coefficient (ICC) and absolute error via the residual standard error (RSE).

Results

Both inter- and intrarater reliability ICCs were at least moderate across all variables (ICC, >0.50), with most movements and corresponding variables having excellent reliability (ICC, >0.90). Although maximum knee valgus angles were the kinematic variables with the lowest interrater reliability (ICCs, 0.59-0.82) and moderate relative agreement, there was agreement in absolute terms with an RSE of <1.3°.

Conclusion

Findings indicated that markerless motion capture provides reliable measurements of joint position during a movement screen, which allows for a more objective evaluation of the direction and subsequent success of interventions. However, practitioners should consider relative and absolute agreements when applying information provided by these systems.

Clinical Relevance

Markerless motion capture systems may assist clinicians by reliably assessing movement screenings using different systems over different collection periods.

Excessive Knee Internal Rotation during Grand Plié in Classical Ballet Female Dancers

Classical ballet dancers are exposed daily to physically demanding movements. Among these, the Grand Plié stands out for its biomechanical complexity, particularly the stress applied to the knee joint. This study investigates the knee kinematics of healthy professional classical ballet dancers performing the Grand Plié. Twenty dancers were evaluated with a motion analysis system using a marker-based protocol. Before measurements, the self-reported Global Knee Functional Assessment Scale was delivered for the knees' functional ability, and the passive range of knee motion was also assessed. The average score on the Global Knee Functional Assessment Scale was 94.65 ± 5.92. During a complete circle of the Grand Plié movement, executed from the upright position, the average maximum internal rotation of the knee joint was 30.28° ± 6.16°, with a simultaneous knee flexion of 134.98° ± 4.62°. This internal rotation observed during knee flexion exceeds the typical range of motion for the joint, suggesting a potential risk for knee injuries, such as meniscal tears. The findings provide an opportunity for future kinematic analysis research, focusing on the movement of the Grand Plié and other common ballet maneuvers. These data have the potential to yield valuable information about the knee kinematics concerning meniscus damage.

Instrumented Pre-Hospital Care Simulation Mannequin for Use in Spinal Motion Restrictions Scenarios: Validation of Cervical and Lumbar Motion Assessment

BACKGROUND

A mid-fidelity simulation mannequin, equipped with an instrumented cervical and lumbar spine, was developed to investigate best practices and train healthcare professionals in applying spinal motion restrictions (SMRs) during the early mobilization and transfer of accident victims with suspected spine injury. The study objectives are to (1) examine accuracy of the cervical and lumbar motions measured with the mannequin; and (2) confirm that the speed of motion has no bearing on this accuracy.

METHODS

Accuracy was evaluated by concurrently comparing the orientation data obtained with the mannequin with that from an optoelectronic system. The mannequin's head and pelvis were moved in all anatomical planes of motion at different speeds.

RESULTS

Accuracy, assessed by root-mean-square error, varied between 0.7° and 1.5° in all anatomical planes of motion. Bland-Altman analysis revealed a bias ranging from -0.7° to 0.6°, with the absolute limit of agreement remaining below 3.5°. The minimal detectable change varied between 1.3° and 2.6°. Motion speed demonstrated no impact on accuracy.

CONCLUSIONS

The results of this validation study confirm the mannequin's potential to provide accurate measurements of cervical and lumbar motion during simulation scenarios for training and research on the application of SMR.

Measuring highly accurate foot position and angle trajectories with foot-mounted IMUs in clinical practice

BACKGROUND

Gait analysis using foot-mounted IMUs is a promising method to acquire gait parameters outside of laboratory settings and in everyday clinical practice. However, the need for precise sensor attachment or calibration, the requirement of environments with a homogeneous magnetic field, and the limited applicability to pathological gait patterns still pose challenges. Furthermore, in previously published work, the measurement accuracy of such systems is often only validated for specific points in time or in a single plane.

RESEARCH QUESTION

This study investigates the measurement accuracy of a gait analysis method based on foot-mounted IMUs in the acquisition of the foot motion, i.e., position and angle trajectories of the foot in the sagittal, frontal, and transversal plane over the entire gait cycle.

RESULTS

A comparison of the proposed method with an optical motion capture system showed an average RMSE of 0.67° for pitch, 0.63° for roll and 1.17° for yaw. For position trajectories, an average RMSE of 0.51 cm for vertical lift and 0.34 cm for lateral shift was found. The measurement error of the IMU-based method is found to be much smaller than the deviations caused by the shoes.

SIGNIFICANCE

The proposed method is found to be sufficiently accurate for clinical practice. It does not require precise mounting, special calibration movements, or magnetometer data, and shows no difference in measurement accuracy between normal and pathological gait. Therefore, it provides an easy-to-use alternative to optical motion capture and facilitates gait analysis independent of laboratory settings.

Using inertial measurement units to estimate spine joint kinematics and kinetics during walking and running

Optical motion capture (OMC) is considered the best available method for measuring spine kinematics, yet inertial measurement units (IMU) have the potential to collect data outside the laboratory. When combined with musculoskeletal modeling, IMU technology may be used to estimate spinal loads in real-world settings. To date, IMUs have not been validated for estimates of spinal movement and loading during both walking and running. Using OpenSim Thoracolumbar Spine and Ribcage models, we compare IMU and OMC estimates of lumbosacral (L5/S1) and thoracolumbar (T12/L1) joint angles, moments, and reaction forces during gait across six speeds for five participants. For comparisons, time series are ensemble averaged over strides. Comparisons between IMU and OMC ensemble averages have low normalized root mean squared errors (< 0.3 for 81% of comparisons) and high, positive cross-correlations (> 0.5 for 91% of comparisons), suggesting signals are similar in magnitude and trend. As expected, joint moments and reaction forces are higher during running than walking for IMU and OMC. Relative to OMC, IMU overestimates joint moments and underestimates joint reaction forces by 20.9% and 15.7%, respectively. The results suggest using a combination of IMU technology and musculoskeletal modeling is a valid means for estimating spinal movement and loading.

Validation of LEOMO inertial measurement unit sensors with marker-based three-dimensional motion capture during maximum sprinting in track cyclists

LEOMO™ is a commercial inertial measurement unit system that provides cycling-specific motion performance indicators (MPIs) and offers a mobile solution for monitoring cyclists. We aimed to validate the LEOMO sensors during sprint cycling using gold-standard marker-based three-dimensional (3D) motion technology (Qualisys, AB). Our secondary aim was to explore the relationship between peak power during sprints and MPIs. Seventeen elite track cyclists performed 3 × 15s seated start maximum efforts on a cycle ergometer. Based on intraclass correlation coefficient (ICC3,1), the MPIs derived from 3D and LEOMO showed moderate agreement (0.50 < 0.75) for the right foot angular range (FAR); left foot angular range first quadrant (FARQ1); right leg angular range (LAR); and mean angle of the pelvis in the sagittal plane. Agreement was poor (ICC < 0.50) between MPIs derived from 3D and LEOMO for the left FAR, right FARQ1, left LAR, and mean range of motion of the pelvis in the frontal and transverse planes. Only one LEOMO-derived (pelvic rotation) and two 3D-derived (right FARQ1 and FAR) MPIs showed large positive significant correlations with peak power. Caution is advised regarding use of the LEOMO for short maximal cycling efforts and derived MPIs to inform peak sprint cycling power production.

Validity of Inertial Measurement Units to Measure Lower-Limb Kinematics and Pelvic Orientation at Submaximal and Maximal Effort Running Speeds

Inertial measurement units (IMUs) have been validated for measuring sagittal plane lower-limb kinematics during moderate-speed running, but their accuracy at maximal speeds remains less understood. This study aimed to assess IMU measurement accuracy during high-speed running and maximal effort sprinting on a curved non-motorized treadmill using discrete (Bland-Altman analysis) and continuous (root mean square error [RMSE], normalised RMSE, Pearson correlation, and statistical parametric mapping analysis [SPM]) metrics. The hip, knee, and ankle flexions and the pelvic orientation (tilt, obliquity, and rotation) were captured concurrently from both IMU and optical motion capture systems, as 20 participants ran steadily at 70%, 80%, 90%, and 100% of their maximal effort sprinting speed (5.36 ± 0.55, 6.02 ± 0.60, 6.66 ± 0.71, and 7.09 ± 0.73 m/s, respectively). Bland-Altman analysis indicated a systematic bias within ±1° for the peak pelvic tilt, rotation, and lower-limb kinematics and -3.3° to -4.1° for the pelvic obliquity. The SPM analysis demonstrated a good agreement in the hip and knee flexion angles for most phases of the stride cycle, albeit with significant differences noted around the ipsilateral toe-off. The RMSE ranged from 4.3° (pelvic obliquity at 70% speed) to 7.8° (hip flexion at 100% speed). Correlation coefficients ranged from 0.44 (pelvic tilt at 90%) to 0.99 (hip and knee flexions at all speeds). Running speed minimally but significantly affected the RMSE for the hip and ankle flexions. The present IMU system is effective for measuring lower-limb kinematics during sprinting, but the pelvic orientation estimation was less accurate.

Upper extremity asymmetry due to nerve injuries or central neurologic conditions: a scoping review

BACKGROUND

Peripheral nerve injuries and central neurologic conditions can result in extensive disabilities. In cases with unilateral impairment, assessing the asymmetry between the upper extremity has been used to assess outcomes of treatment and severity of injury. A wide variety of validated and novel tests and sensors have been utilized to determine the upper extremity asymmetry. The purpose of this article is to review the literature and define the current state of the art for describing upper extremity asymmetry in patients with peripheral nerve injuries or central neurologic conditions.

METHOD

An electronic literature search of PubMed, Scopus, Web of Science, OVID was performed for publications between 2000 to 2022. Eligibility criteria were subjects with neurological conditions/injuries who were analyzed for dissimilarities in use between the upper extremities. Data related to study population, target condition/injury, types of tests performed, sensors used, real-world data collection, outcome measures of interest, and results of the study were extracted. Sackett's Level of Evidence was used to judge the quality of the articles.

RESULTS

Of the 7281 unique articles, 112 articles met the inclusion criteria for the review. Eight target conditions/injuries were identified (Brachial Plexus Injury, Cerebral Palsy, Multiple Sclerosis, Parkinson's Disease, Peripheral Nerve Injury, Spinal Cord Injury, Schizophrenia, and stroke). The tests performed were classified into thirteen categories based on the nature of the test and data collected. The general results related to upper extremity asymmetry were listed for all the reviewed articles. Stroke was the most studied condition, followed by cerebral palsy, with kinematics and strength measurement tests being the most frequently used tests. Studies with a level of evidence level II and III increased between 2000 and 2021. The use of real-world evidence-based data, and objective data collection tests also increased in the same period.

CONCLUSION

Adequately powered randomized controlled trials should be used to study upper extremity asymmetry. Neurological conditions other than stroke should be studied further. Upper extremity asymmetry should be measured using objective outcome measures like motion tracking and activity monitoring in the patient's daily living environment.

Human Posture Estimation: A Systematic Review on Force-Based Methods-Analyzing the Differences in Required Expertise and Result Benefits for Their Utilization

Force-based human posture estimation (FPE) provides a valuable alternative when camera-based human motion capturing is impractical. It offers new opportunities for sensor integration in smart products for patient monitoring, ergonomic optimization and sports science. Due to the interdisciplinary research on the topic, an overview of existing methods and the required expertise for their utilization is lacking. This paper presents a systematic review by the PRISMA 2020 review process. In total, 82 studies are selected (59 machine learning (ML)-based and 23 digital human model (DHM)-based posture estimation methods). The ML-based methods use input data from hardware sensors-mostly pressure mapping sensors-and trained ML models for estimating human posture. The ML-based human posture estimation algorithms mostly reach an accuracy above 90%. DHMs, which represent the structure and kinematics of the human body, adjust posture to minimize physical stress. The required expert knowledge for the utilization of these methods and their resulting benefits are analyzed and discussed. DHM-based methods have shown their general applicability without the need for application-specific training but require expertise in human physiology. ML-based methods can be used with less domain-specific expertise, but an application-specific training of these models is necessary.

Interchangeability of optical tracking technologies: potential overestimation of the sprint running load demands in the English Premier League

PURPOSE

The purpose of this study was to assess the agreement between match-derived running load outputs; total distance (TD), high-speed running (HSR) and sprint distance (SPR) obtained by two optical tracking systems.

METHODS

Data were collected from 31 elite footballers from the first team and under-21 squads of an English Premier League (EPL) football club across three competitive matches. One EPL game (game 2) and one under-21 Premier League game (game 3) were played at the team's home stadium and one EPL game (game 1) at an away venue. All matches were tracked concomitantly using eight colour cameras sampling at 10 Hz (PROZONE®) and six high-definition motion cameras sampling at 25 Hz (TRACAB®).

RESULTS

TD displayed a perfect (r = 0.99) correlation while HSR and SPR displayed very large (r = 0.81 and r = 0.73) correlations between TRACAB® and PROZONE®. Mean biases were 5% for TD, -3% for HSR and 61% for SPR. Between games, mean biases for TD were 6% for game 1, and 5% for game 2 and game 3. For HSR, 9% for game 1, -5% for game 2 and 6% for game 3 and for SPR, 31% for game 1, 71% for game 2 and 84% for game 3.

CONCLUSION

TD and HSR can be interchanged between PROZONE® and TRACAB®, to allow accurate interpretation between the two optical systems. PROZONE® overestimated SPR compared to the TRACAB®, with the magnitude of difference considered meaningful, altering interpretation of historical match outputs, sprint volume trends in the EPL and forecasts of the modern game.

Development of a Methodology for Low-Cost 3D Underwater Motion Capture: Application to the Biomechanics of Horse Swimming

Hydrotherapy has been utilized in horse rehabilitation programs for over four decades. However, a comprehensive description of the swimming cycle of horses is still lacking. One of the challenges in studying this motion is 3D underwater motion capture, which holds potential not only for understanding equine locomotion but also for enhancing human swimming performance. In this study, a marker-based system that combines underwater cameras and markers drawn on horses is developed. This system enables the reconstruction of the 3D motion of the front and hind limbs of six horses throughout an entire swimming cycle, with a total of twelve recordings. The procedures for pre- and post-processing the videos are described in detail, along with an assessment of the estimated error. This study estimates the reconstruction error on a checkerboard and computes an estimated error of less than 10 mm for segments of tens of centimeters and less than 1 degree for angles of tens of degrees. This study computes the 3D joint angles of the front limbs (shoulder, elbow, carpus, and front fetlock) and hind limbs (hip, stifle, tarsus, and hind fetlock) during a complete swimming cycle for the six horses. The ranges of motion observed are as follows: shoulder: 17 ± 3°; elbow: 76 ± 11°; carpus: 99 ± 10°; front fetlock: 68 ± 12°; hip: 39 ± 3°; stifle: 68 ± 7°; tarsus: 99 ± 6°; hind fetlock: 94 ± 8°. By comparing the joint angles during a swimming cycle to those observed during classical gaits, this study reveals a greater range of motion (ROM) for most joints during swimming, except for the front and hind fetlocks. This larger ROM is usually achieved through a larger maximal flexion angle (smaller minimal angle of the joints). Finally, the versatility of the system allows us to imagine applications outside the scope of horses, including other large animals and even humans.

Validity and Reliability of Polar Team Pro and Playermaker for Estimating Running Distance and Speed in Indoor and Outdoor Conditions

Although global positioning systems and inertial measurement unit systems are often used to quantify physical variables in training, both types of systems need to be compared, considering their frequent use in measuring physical loads. Thus, the purpose of our study was to test the reliability and validity of speed and distance run measurements at different intensities in indoor and outdoor conditions made by Polar Team Pro and Playermaker. Four participants (age = 30.0 ± 5.1 years, body mass = 76.3 ± 5.3 kg, height = 1.79 ± 0.09 m), each wearing three Polar Team Pro and two Playermaker sensors, performed 100 m runs with different prescribed intensities (i.e., criterion measure) varying from 8 to 24 km h-1, in a straight line and/or rectangle under indoor and outdoor conditions. Both systems underestimated total distance; Playermaker underestimated speed, the extent of which increased as speed increased, while Polar Team Pro overestimated mean speed at 8 km h-1 for the straight-line condition. No differences emerged in mean speed estimated by Polar Team Pro at any intensities other than 20 km h-1, which was underestimated by 2%. The reliability of the sensors was good, given a coefficient of variation (CV) of <2% for all conditions except when measuring indoor conditions with Polar Team Pro (CV ≈ 10%). Intraclass correlations (ICCs) for consistency within the sensors varied from 0.47 to 0.99, and significantly lower ICCs were documented at 8, 10, and 12 km h-1. Both systems underestimated distance measured in indoor and outdoor conditions, and distance validity in different intensities seemed to worsen as speeds increased. Although Polar Team Pro demonstrated poor validity and reliability in indoor conditions, both systems exhibited good reliability between their sensors in outdoor conditions, whereas the reliability within their sensors varied with different speeds.

Sit-to-walk strategy classification in healthy adults using hip and knee joint angles at gait initiation

Forward continuation, balance, and sit-to-stand-and-walk (STSW) are three common movement strategies during sit-to-walk (STW) executions. Literature identifies these strategies through biomechanical parameters using gold standard laboratory equipment, which is expensive, bulky, and requires significant post-processing. STW strategy becomes apparent at gait-initiation (GI) and the hip/knee are primary contributors in STW, therefore, this study proposes to use the hip/knee joint angles at GI as an alternate method of strategy classification. To achieve this, K-means clustering was implemented using three clusters corresponding to the three STW strategies; and two feature sets corresponding to the hip/knee angles (derived from motion capture data); from an open access online database (age: 21-80 years; n = 10). The results identified forward continuation with the lowest hip/knee extension, followed by balance and then STSW, at GI. Using this classification, strategy biomechanics were investigated by deriving the established biomechanical quantities from literature. The biomechanical parameters that significantly varied between strategies (P < 0.05) were time, horizontal centre of mass (COM) momentum, braking impulse, centre of pressure (COP) range and velocities, COP-COM separation, hip/knee torque and movement fluency. This alternate method of strategy classification forms a generalized framework for describing STW executions and is consistent with literature, thus validating the joint angle classification method.

Application of IoT technology based on neural networks in basketball training motion capture and injury prevention

Basketball players need to frequently engage in various physical movements during the game, which puts a certain burden on their bodies and can easily lead to various sports injuries. Therefore, it is crucial to prevent sports injuries in basketball teaching. This paper also studies basketball motion track capture. Basketball motion capture preserves the motion posture information of the target person in three-dimensional space. Because the motion capture system based on machine vision often encounters problems such as occlusion or self occlusion in the application scene, human motion capture is still a challenging problem in the current research field. This article designs a multi perspective human motion trajectory capture algorithm framework, which uses a two-dimensional human motion pose estimation algorithm based on deep learning to estimate the position distribution of human joint points on the two-dimensional image from each perspective. By combining the knowledge of camera poses from multiple perspectives, the three-dimensional spatial distribution of joint points is transformed, and the final evaluation result of the target human 3D pose is obtained. This article applies the research results of neural networks and IoT devices to basketball motion capture methods, further developing basketball motion capture systems.

Analysis of Fluency of Movement in Parkour Using a Video and Inertial Measurement Unit Technology

Fluency is a movement parameter combining smoothness and hesitation, and its objective measurement may be used to determine the effects of practice on sports performance. This study aimed to measure fluency in parkour, an acrobatic discipline comprising complex non-cyclical movements, which involves fluency as a critical aspect of performance. Inter-individual fluidity differences between advanced and novice athletes as well as intra-individual variations of fluency between different parts and subsequent repetitions of a path were addressed. Seventeen parkour participants were enrolled and divided into two groups based on their experience. We analysed signals captured from an inertial measurement unit fixed on the back of the pelvis of each participant during three consecutive repetitions of a specifically designed parkour routine under the guidance of video analysis. Two fluency parameters, namely smoothness and hesitation, were measured. Smoothness was calculated as the number of inflexions on the so-called jerk graph; hesitation was the percentage of the drop in the centre of mass velocity. Smoothness resulted in significantly lower values in advanced athletes (mean: 126.4; range: 36-192) than in beginners (mean: 179.37; range: 98-272) during one of the three motor activities (p = 0.02). A qualitative analysis of hesitation showed that beginner athletes tended to experience more prominent velocity drops and negative deflection than more advanced athletes. In conclusion, a system based on a video and an inertial measurement unit is a promising approach for quantification and the assessment of variability of fluency, and it is potentially beneficial to guide and evaluate the training process.

Mechanical Determinants of Sprinting and Change of Direction in Elite Female Field Hockey Players

Profile determination in field hockey is critical to determining athletes' physical strengths and weaknesses, and is key in planning, programming, and monitoring training. This study pursued two primary objectives: (i) to provide descriptive data on sprinting, deceleration, and change of direction (COD) abilities and (ii) to elucidate the mechanical variables that influence sprint and COD performance in elite female field hockey players. Using radar and time-gate technology, we assessed performance and mechanical data from 30 m sprinting, deceleration, and COD tests for 26 elite female hockey players. A machine learning approach identified mechanical variables related to sprint and COD performance. Our findings offer a framework for athlete categorization and the design of performance-enhancing training strategies at the international level. Two pivotal mechanical variables-relative maximum horizontal force (F0) and maximum velocity (Vmax)-predominantly influence the times across all tested distances. However, the force-velocity profile (FVP) and horizontal deceleration do not influence the variance in the COD test outcomes. These insights can guide the design, adjustment, and monitoring of training programs, assisting coaches in decision making to optimize performance and mitigate injury risks for female hockey players.

Integrated UWB/MIMU Sensor System for Position Estimation towards an Accurate Analysis of Human Movement: A Technical Review

Integrated Ultra-wideband (UWB) and Magnetic Inertial Measurement Unit (MIMU) sensor systems have been gaining popularity for pedestrian tracking and indoor localization applications, mainly due to their complementary error characteristics that can be exploited to achieve higher accuracies via a data fusion approach. These integrated sensor systems have the potential for improving the ambulatory 3D analysis of human movement (estimating 3D kinematics of body segments and joints) over systems using only on-body MIMUs. For this, high accuracy is required in the estimation of the relative positions of all on-body integrated UWB/MIMU sensor modules. So far, these integrated UWB/MIMU sensors have not been reported to have been applied for full-body ambulatory 3D analysis of human movement. Also, no review articles have been found that have analyzed and summarized the methods integrating UWB and MIMU sensors for on-body applications. Therefore, a comprehensive analysis of this technology is essential to identify its potential for application in 3D analysis of human movement. This article thus aims to provide such a comprehensive analysis through a structured technical review of the methods integrating UWB and MIMU sensors for accurate position estimation in the context of the application for 3D analysis of human movement. The methods used for integration are all summarized along with the accuracies that are reported in the reviewed articles. In addition, the gaps that are required to be addressed for making this system applicable for the 3D analysis of human movement are discussed.

Motion Capture Technologies for Ergonomics: A Systematic Literature Review

Muscular skeletal disorder is a difficult challenge faced by the working population. Motion capture (MoCap) is used for recording the movement of people for clinical, ergonomic and rehabilitation solutions. However, knowledge barriers about these MoCap systems have made them difficult to use for many people. Despite this, no state-of-the-art literature review on MoCap systems for human clinical, rehabilitation and ergonomic analysis has been conducted. A medical diagnosis using AI applies machine learning algorithms and motion capture technologies to analyze patient data, enhancing diagnostic accuracy, enabling early disease detection and facilitating personalized treatment plans. It revolutionizes healthcare by harnessing the power of data-driven insights for improved patient outcomes and efficient clinical decision-making. The current review aimed to investigate: (i) the most used MoCap systems for clinical use, ergonomics and rehabilitation, (ii) their application and (iii) the target population. We used preferred reporting items for systematic reviews and meta-analysis guidelines for the review. Google Scholar, PubMed, Scopus and Web of Science were used to search for relevant published articles. The articles obtained were scrutinized by reading the abstracts and titles to determine their inclusion eligibility. Accordingly, articles with insufficient or irrelevant information were excluded from the screening. The search included studies published between 2013 and 2023 (including additional criteria). A total of 40 articles were eligible for review. The selected articles were further categorized in terms of the types of MoCap used, their application and the domain of the experiments. This review will serve as a guide for researchers and organizational management.

Foot rotation and pelvic angle correlate with knee abduction moment during 180° lateral cut in football players

BACKGROUND

Lateral movements are challenging for 2D video-analysis and are therefore often omitted in functional tests for Anterior Cruciate Ligament (ACL) injury risk assessment. The purpose of the present study was to investigate the association between frontal and transverse plane angles obtained from 2D video-analysis and knee abduction moment (KAM) from gold standard 3D motion capture in a 180° lateral cut task. The hypothesis was that 2D angles other than the knee joint effectively explain variations in KAM.

METHODS

Thirty-four healthy football players (age 22.8 ± 4.1 years) performed a series of 180° lateral cut (lateral shuffles) tasks. The peak KAM was collected through a 3D motion capture system. A 2D video-analysis movement assessment identified frontal and transverse plane joint kinematics: foot projection angle (FPA), Frontal Plane Knee Projection Angle (FPKPA), Pelvis tilt angle (PA), and Trunk tilt angle (TA). A forward stepwise regression model was used to assess significant 2D predictors of KAM (p < 0.05).

RESULTS

FPA and PA were the only significant predictors (R2-ajdusted = 9.2%, p < 0.001), with external foot rotation and contralateral pelvic drop associated with higher KAM. Based on the regression model, the "High FPA & PA group" was defined and showed higher KAM than the rest of the cohort (p = 0.012, ES = 0.71).

CONCLUSIONS

The external foot rotation and the contralateral pelvic drop from 2D video-analysis were associated with higher peak KAM during the 180° lateral cut. A qualitative assessment of the 180° lateral cut could offer precious insights on ACL injury risk mitigation.

LEVEL OF EVIDENCE

Descriptive Laboratory Study.

Conversion of Upper-Limb Inertial Measurement Unit Data to Joint Angles: A Systematic Review

Inertial measurement units (IMUs) have become the mainstay in human motion evaluation outside of the laboratory; however, quantification of 3-dimensional upper limb motion using IMUs remains challenging. The objective of this systematic review is twofold. Firstly, to evaluate computational methods used to convert IMU data to joint angles in the upper limb, including for the scapulothoracic, humerothoracic, glenohumeral, and elbow joints; and secondly, to quantify the accuracy of these approaches when compared to optoelectronic motion analysis. Fifty-two studies were included. Maximum joint motion measurement accuracy from IMUs was achieved using Euler angle decomposition and Kalman-based filters. This resulted in differences between IMU and optoelectronic motion analysis of 4° across all degrees of freedom of humerothoracic movement. Higher accuracy has been achieved at the elbow joint with functional joint axis calibration tasks and the use of kinematic constraints on gyroscope data, resulting in RMS errors between IMU and optoelectronic motion for flexion-extension as low as 2°. For the glenohumeral joint, 3D joint motion has been described with RMS errors of 6° and higher. In contrast, scapulothoracic joint motion tracking yielded RMS errors in excess of 10° in the protraction-retraction and anterior-posterior tilt direction. The findings of this study demonstrate high-quality 3D humerothoracic and elbow joint motion measurement capability using IMUs and underscore the challenges of skin motion artifacts in scapulothoracic and glenohumeral joint motion analysis. Future studies ought to implement functional joint axis calibrations, and IMU-based scapula locators to address skin motion artifacts at the scapula, and explore the use of artificial neural networks and data-driven approaches to directly convert IMU data to joint angles.

Concurrent validity and between-unit reliability of a foot-mounted inertial measurement unit to measure velocity during team sport activity

The concurrent validity and between-unit reliability of a foot-mounted inertial measurement unit (F-IMU) was investigated during linear and change of direction running drills. Sixteen individuals performed four repetitions of two drills (maximal acceleration and flying 10 m sprint) and five repetitions of a multi-directional movement protocol. Participants wore two F-IMUs (Playermaker) and 10 retro-reflective markers to allow for comparisons to the criterion system (Qualisys). Validity of the F-IMU derived velocity was assessed via root-mean-square error (RMSE), 95% limits of agreement (LoA) and mean difference with 95% confidence interval (CI). Between-unit reliability was assessed via intraclass correlation (ICC) with 90% CI and 95% LoA. The mean difference for instantaneous velocity for all participants and drills combined was -0.048 ± 0.581 m ∙ s^-1, the LoA were from -1.09 to -1.186 m ∙ s^-1 and RMSE was 0.583 m ∙ s^-1. The ICC ranged from 0.84 to 1, with LoA from -7.412 to 2.924 m ∙ s^-1. Differences were dependent on the reference speed, with the greatest absolute difference (-0.66 m ∙ s^-1) found at velocities above 7 m ∙ s^-1. Between-unit reliability of the F-IMU ranges from good to excellent for all locomotor characteristics. Playermaker has good agreement with 3D motion capture for velocity and good to excellent between-unit reliability.

Kinematic evaluation and reliability assessment of the Nine Hole Peg Test for manual dexterity

BACKGROUND

The Nine Hole Peg Test (NHPT) is one of the most frequently used tools to assess manual dexterity. However, no kinematic parameters are provided to describe the quality of the motor performance, since time is the only score.

PURPOSE

To investigate test-retest and intra-rater reliability, correlation with clinical test score, and discriminant validity of kinematic indexes during NHPT.

STUDY DESIGN

A clinical measurement study.

METHODS

Twenty-five healthy right-handed volunteers performed the NHPT. An experienced physiotherapist administered two sessions at a 6-hour interval with two trials for dominant and non-dominant upper limbs. An optoelectronic system was used to detect NHPT performance, which was divided into nine consecutive peg-grasp, peg-transfer, peg-in-hole, hand-return phases, and one final removing phase. Outcome measures were total and single phases times, normalized jerk, mean, peak and time-to-peak of velocity, curvature index during peg-grasp and hand-return phases, and trunk 3D displacement. The statistical analysis included Intraclass Correlation Coefficients (ICCs) for test-retest and intra-rater reliability, Pearson's coefficients for correlation with the NHPT score, and paired t-tests for discriminant validity.

RESULTS

Test-retest reliability was excellent for trunk rotation (ICC: 0.91) and good to moderate for the other indexes (ICCs: 0.89-0.61). Intra-rater reliability was excellent for total and removing times (ICCs: 0.91 and 0.94) and good to moderate for the other indexes (ICCs: 0.84-0.66), except for trunk inclination (ICC: 0.37). NHPT phases, normalized jerk, mean velocity, peak of velocity, time-to-peak and curvature index correlated with total time (r-score: 0.8-0.3). NHPT phases and most kinematic indexes discriminated the dominant from non-dominant upper limb, with the greatest effect size for normalized jerk during hand-return (d = 1.16).

CONCLUSIONS

Kinematic indexes during NHPT can be considered for manual dexterity assessment. These indexes may allow for the detection of kinematic changes responsible for NHPT score variations in healthy subjects or patients with upper limb impairments.

A Review of Intelligent Assembly Technology of Small Electronic Equipment

Electronic equipment, including phased array radars, satellites, high-performance computers, etc., has been widely used in military and civilian fields. Its importance and significance are self-evident. Electronic equipment has many small components, various functions, and complex structures, making assembly an essential step in the manufacturing process of electronic equipment. In recent years, the traditional assembly methods have had difficulty meeting the increasingly complex assembly needs of military and civilian electronic equipment. With the rapid development of Industry 4.0, emerging intelligent assembly technology is replacing the original "semi-automatic" assembly technology. Aiming at the assembly requirements of small electronic equipment, we first evaluate the existing problems and technical difficulties. Then, we analyze the intelligent assembly technology of electronic equipment from three aspects: visual positioning, path and trajectory planning, and force-position coordination control technology. Further, we describe and summarize the research status and the application of the technology and discuss possible future research directions in the intelligent assembly technology of small electronic equipment.

Level of Agreement between the MotionMetrix System and an Optoelectronic Motion Capture System for Walking and Running Gait Measurements

Markerless motion capture systems (MCS) have been developed as an alternative solution to overcome the limitations of 3D MCS as they provide a more practical and efficient setup process given, among other factors, the lack of sensors attached to the body. However, this might affect the accuracy of the measures recorded. Thus, this study is aimed at evaluating the level of agreement between a markerless MSC (i.e., MotionMetrix) and an optoelectronic MCS (i.e., Qualisys). For such purpose, 24 healthy young adults were assessed for walking (at 5 km/h) and running (at 10 and 15 km/h) in a single session. The parameters obtained from MotionMetrix and Qualisys were tested in terms of level of agreement. When walking at 5 km/h, the MotionMetrix system significantly underestimated the stance and swing phases, as well as the load and pre-swing phases (p < 0.05) reporting also relatively low systematic bias (i.e., ≤ -0.03 s) and standard error of the estimate (SEE) (i.e., ≤0.02 s). The level of agreement between measurements was perfect (r > 0.9) for step length left and cadence and very large (r > 0.7) for step time left, gait cycle, and stride length. Regarding running at 10 km/h, bias and SEE analysis revealed significant differences for most of the variables except for stride time, rate and length, swing knee flexion for both legs, and thigh flexion left. The level of agreement between measurements was very large (r > 0.7) for stride time and rate, stride length, and vertical displacement. At 15 km/h, bias and SEE revealed significant differences for vertical displacement, landing knee flexion for both legs, stance knee flexion left, thigh flexion, and extension for both legs. The level of agreement between measurements in running at 15 km/h was almost perfect (r > 0.9) when comparing Qualisys and MotionMetrix parameters for stride time and rate, and stride length. The agreement between the two motion capture systems varied for different variables and speeds of locomotion, with some variables demonstrating high agreement while others showed poor agreement. Nonetheless, the findings presented here suggest that the MotionMetrix system is a promising option for sports practitioners and clinicians interested in measuring gait variables, particularly in the contexts examined in the study.

Use, Validity and Reliability of Inertial Movement Units in Volleyball: Systematic Review of the Scientific Literature

The use of inertial devices in sport has become increasingly common. The aim of this study was to examine the validity and reliability of multiple devices for measuring jump height in volleyball. The search was carried out in four databases (PubMed, Scopus, Web of Sciences and SPORTDiscus) using keywords and Boolean operators. Twenty-one studies were selected that met the established selection criteria. The studies focused on determining the validity and reliability of IMUs (52.38%), on controlling and quantifying external load (28.57%) and on describing differences between playing positions (19.05%). Indoor volleyball was the modality in which IMUs have been used the most. The most evaluated population was elite, adult and senior athletes. The IMUs were used both in training and in competition, evaluating mainly the amount of jump, the height of the jumps and some biomechanical aspects. Criteria and good validity values for jump counting are established. The reliability of the devices and the evidence is contradictory. IMUs are devices used in volleyball to count and measure vertical displacements and/or compare these measurements with the playing position, training or to determine the external load of the athletes. It has good validity measures, although inter-measurement reliability needs to be improved. Further studies are suggested to position IMUs as measuring instruments to analyze jumping and sport performance of players and teams.

Development of a Real-Time 6-DOF Motion-Tracking System for Robotic Computer-Assisted Implant Surgery

In this paper, we investigate a motion-tracking system for robotic computer-assisted implant surgery. Failure of the accurate implant positioning may result in significant problems, thus an accurate real-time motion-tracking system is crucial for avoiding these issues in computer-assisted implant surgery. Essential features of the motion-tracking system are analyzed and classified into four categories: workspace, sampling rate, accuracy, and back-drivability. Based on this analysis, requirements for each category have been derived to ensure that the motion-tracking system meets the desired performance criteria. A novel 6-DOF motion-tracking system is proposed which demonstrates high accuracy and back-drivability, making it suitable for use in computer-assisted implant surgery. The results of the experiments confirm the effectiveness of the proposed system in achieving the essential features required for a motion-tracking system in robotic computer-assisted implant surgery.

Face touch monitoring using an instrumented wristband using dynamic time warping and k-nearest neighbours

One of the main factors in controlling infectious diseases such as COVID-19 is to prevent touching preoral and prenasal regions. Face touching is a habitual behaviour that occurs frequently. Studies showed that people touch their faces 23 times per hour on average. A contaminated hand could transmit the infection to the body by a facial touch. Since controlling this spontaneous habit is not easy, this study aimed to develop and validate a technology to detect and monitor face touch using dynamic time warping (DTW) and KNN (k-nearest neighbours) based on a wrist-mounted inertial measurement unit (IMU) in a controlled environment and natural environment trials. For this purpose, eleven volunteers were recruited and their hand motions were recorded in controlled and natural environment trials using a wrist-mounted IMU. Then the sensitivity, precision, and accuracy of our developed technology in detecting the face touch were evaluated. It was observed that the sensitivity, precision, and accuracy of the DTW-KNN classifier were 91%, 97%, and 85% in controlled environment trials and 79%, 92%, and 79% in natural environment trials (daily life). In conclusion, a wrist-mounted IMU, widely available in smartwatches, could detect the face touch with high sensitivity, precision, and accuracy and can be used as an ambulatory system to detect and monitor face touching as a high-risk habit in daily life.

Definition of High-Risk Motion Patterns for Female ACL Injury Based on Football-Specific Field Data: A Wearable Sensors Plus Data Mining Approach

The aim of the present study was to investigate if the presence of anterior cruciate ligament (ACL) injury risk factors depicted in the laboratory would reflect at-risk patterns in football-specific field data. Twenty-four female footballers (14.9 ± 0.9 year) performed unanticipated cutting maneuvers in a laboratory setting and on the football pitch during football-specific exercises (F-EX) and games (F-GAME). Knee joint moments were collected in the laboratory and grouped using hierarchical agglomerative clustering. The clusters were used to investigate the kinematics collected on field through wearable sensors. Three clusters emerged: Cluster 1 presented the lowest knee moments; Cluster 2 presented high knee extension but low knee abduction and rotation moments; Cluster 3 presented the highest knee abduction, extension, and external rotation moments. In F-EX, greater knee abduction angles were found in Cluster 2 and 3 compared to Cluster 1 (p = 0.007). Cluster 2 showed the lowest knee and hip flexion angles (p < 0.013). Cluster 3 showed the greatest hip external rotation angles (p = 0.006). In F-GAME, Cluster 3 presented the greatest knee external rotation and lowest knee flexion angles (p = 0.003). Clinically relevant differences towards ACL injury identified in the laboratory reflected at-risk patterns only in part when cutting on the field: in the field, low-risk players exhibited similar kinematic patterns as the high-risk players. Therefore, in-lab injury risk screening may lack ecological validity.

A Minimal Sensor Inertial Measurement Unit System Is Replicable and Capable of Estimating Bilateral Lower-Limb Kinematics in a Stationary Bodyweight Squat and a Countermovement Jump

This study aimed to validate a 7-sensor inertial measurement unit system against optical motion capture to estimate bilateral lower-limb kinematics. Hip, knee, and ankle sagittal plane peak angles and range of motion (ROM) were compared during bodyweight squats and countermovement jumps in 18 participants. In the bodyweight squats, left peak hip flexion (intraclass correlation coefficient [ICC] = .51), knee extension (ICC = .68) and ankle plantar flexion (ICC = .55), and hip (ICC = .63) and knee (ICC = .52) ROM had moderate agreement, and right knee ROM had good agreement (ICC = .77). Relatively higher agreement was observed in the countermovement jumps compared to the bodyweight squats, moderate to good agreement in right peak knee flexion (ICC = .73), and right (ICC = .75) and left (ICC = .83) knee ROM. Moderate agreement was observed for right ankle plantar flexion (ICC = .63) and ROM (ICC = .51). Moderate agreement (ICC > .50) was observed in all variables in the left limb except hip extension, knee flexion, and dorsiflexion. In general, there was poor agreement for peak flexion angles, and at least moderate agreement for joint ROM. Future work will aim to optimize methodologies to increase usability and confidence in data interpretation by minimizing variance in system-based differences and may also benefit from expanding planes of movement.

Accuracy and feasibility of a novel fine hand motor skill assessment using computer vision object tracking

We developed a computer vision-based three-dimension (3D) motion capture system employing two action cameras to examine fine hand motor skill by tracking an object manipulated by a hand. This study aimed to examine the accuracy and feasibility of this approach for detecting changes in a fine hand motor skill. We conducted three distinct experiments to assess the system's accuracy and feasibility. We employed two high-resolution, high-frame-rate action cameras. We evaluated the accuracy of our system in calculating the 3D locations of moving object in various directions. We also examined the system's feasibility in identifying improvement in fine hand motor skill after practice in eleven non-disabled young adults. We utilized color-based object detection and tracking to estimate the object's 3D location, and then we computed the object's kinematics, representing the endpoint goal-directed arm reaching movement. Compared to ground truth measurements, the findings demonstrated that our system can adequately estimate the 3D locations of a moving object. We also showed that the system can be used to measure the endpoint kinematics of goal-directed arm reaching movements to detect changes in fine hand motor skill after practice. Future research is needed to confirm the system's reliability and validity in assessing fine hand motor skills in patient populations.

Non-human primate models and systems for gait and neurophysiological analysis

Brain-computer interfaces (BCIs) have garnered extensive interest and become a groundbreaking technology to restore movement, tactile sense, and communication in patients. Prior to their use in human subjects, clinical BCIs require rigorous validation and verification (V&V). Non-human primates (NHPs) are often considered the ultimate and widely used animal model for neuroscience studies, including BCIs V&V, due to their proximity to humans. This literature review summarizes 94 NHP gait analysis studies until 1 June, 2022, including seven BCI-oriented studies. Due to technological limitations, most of these studies used wired neural recordings to access electrophysiological data. However, wireless neural recording systems for NHPs enabled neuroscience research in humans, and many on NHP locomotion, while posing numerous technical challenges, such as signal quality, data throughout, working distance, size, and power constraint, that have yet to be overcome. Besides neurological data, motion capture (MoCap) systems are usually required in BCI and gait studies to capture locomotion kinematics. However, current studies have exclusively relied on image processing-based MoCap systems, which have insufficient accuracy (error: ≥4° and 9 mm). While the role of the motor cortex during locomotion is still unclear and worth further exploration, future BCI and gait studies require simultaneous, high-speed, accurate neurophysiological, and movement measures. Therefore, the infrared MoCap system which has high accuracy and speed, together with a high spatiotemporal resolution neural recording system, may expand the scope and improve the quality of the motor and neurophysiological analysis in NHPs.

A Wearable-Sensor System with AI Technology for Real-Time Biomechanical Feedback Training in Hammer Throw

Developing real-time biomechanical feedback systems for in-field applications will transfer human motor skills' learning/training from subjective (experience-based) to objective (science-based). The translation will greatly improve the efficiency of human motor skills' learning and training. Such a translation is especially indispensable for the hammer-throw training which still relies on coaches' experience/observation and has not seen a new world record since 1986. Therefore, we developed a wearable wireless sensor system combining with artificial intelligence for real-time biomechanical feedback training in hammer throw. A framework was devised for developing such practical wearable systems. A printed circuit board was designed to miniaturize the size of the wearable device, where an Arduino microcontroller, an XBee wireless communication module, an embedded load cell and two micro inertial measurement units (IMUs) could be inserted/connected onto the board. The load cell was for measuring the wire tension, while the two IMUs were for determining the vertical displacements of the wrists and the hip. After calibration, the device returned a mean relative error of 0.87% for the load cell and the accuracy of 6% for the IMUs. Further, two deep neural network models were built to estimate selected joint angles of upper and lower limbs related to limb coordination based on the IMUs' measurements. The estimation errors for both models were within an acceptable range, i.e., approximately ±12° and ±4°, respectively, demonstrating strong correlation existed between the limb coordination and the IMUs' measurements. The results of the current study suggest a remarkable novelty: the difficulty-to-measure human motor skills, especially in those sports involving high speed and complex motor skills, can be tracked by wearable sensors with neglect movement constraints to the athletes. Therefore, the application of artificial intelligence in a wearable system has shown great potential of establishing real-time biomechanical feedback training in various sports. To our best knowledge, this is the first practical research of combing wearables and machine learning to provide biomechanical feedback in hammer throw. Hopefully, more wearable biomechanical feedback systems integrating artificial intelligence would be developed in the future.

Optimal Drop Height in Prepubertal Boys Is Revealed by the Performance in Squat Jump

Drop jump (DJ) performance gain with increasing drop height is well documented in adults, but there is still no clear evidence of such gain in children. This study aimed to examine the differences in DJ performance gain in male adults and prepubescent boys by comparing drop heights tailored to each individual's performance and expressed as a percentage of their squat jump (SJ) performance. Fifteen boys (9-11 y) and 15 men (19-27 y) executed DJs from drop heights that were set at 75%, 100%, 125%, and 150% of their best performance in SJ (DJ75, DJ100, DJ125, and DJ150, respectively). Vertical ground reaction force (vGRF), contact time and kinematics of the lower extremities were captured. The results showed that boys jumped significantly lower than adults in DJs, and both age groups presented jumping gain with increasing drop height, up to DJ125. Boys demonstrated longer total contact time, lower angular velocity and vGRF during the propulsive phase, as well as smaller knee flexion at touchdown and lower reactive strength index. vGRF in DJ75 and DJ100 was lower than in DJ125 and DJ150. The highest value for maximum knee flexion was also presented at DJ150. It is concluded that in prepubescent boys, the appropriate drop height for an effective DJ is linked to their performance in SJ and might be between 75% and 125% of their maximum SJ performance.

A multi-club analysis of the locomotor training characteristics of elite female soccer players

OBJECTIVE

Quantifying differences in locomotor characteristics of training between two competition levels and between training days within elite female soccer players.

METHODS

Foot-mounted inertial measurement unit (Playermaker) data were collected from 293 players from three Women's Super League (WSL; n = 76) and eight Women's Championship (WC; n = 217) teams over a 28-week period. Data were analysed using partial least squares correlation analysis to identify relative variable importance and linear mixed effects models to identify magnitude of effects.

RESULTS

WSL players performed more high-speed running distance (HSR; >5.29 m∙s^-1), sprint distance (SpD; >6.26 m∙s^-1), acceleration (ACC; >3 m∙s^-2) and deceleration (DEC; <-3 m∙s^-2) distance than WC players. The largest difference between WSL and WC in HSR and HSR per minute occurred on MD-4, (354.7 vs. 190.29 m and 2.8 vs. 1.7 m∙min^-1). On MD-2, WSL players also covered greater SpD (44.66 vs. 12.42 m), SpD per minute (0.38 vs. 0.11 m∙min^-1) and HSR per minute (1.67 vs. 0.93 m∙min^-1). Between training days both WSL and WC teams reduced HSR and SpD but not ACC and DEC distance from MD-4 to MD-2, with MD-4 the highest training day of the week.

CONCLUSION

MD-4 is a key training day discriminating between competitive level. HSR and SpD volume and intensity is tapered in WSL and WC players, however there is less clear taper of ACC or DEC. As such, WC teams could increase the volume and intensity of HSR on MD-4 to mimic locomotor activities of those at a higher standard.

Elevated hip adduction angles and abduction moments in the gait of adolescents with recurrent patellar dislocation

INTRODUCTION

Impaired hip kinematics and kinetics may incite patellar instability. This study tested the hypothesis that hip adduction and internal rotation angles during gait are higher in adolescents with recurrent patellar dislocations compared to healthy controls.

MATERIAL AND METHODS

Case-control study. Eighty-eight knees (67 patients) with recurrent patellar dislocation (mean age 14.8 years ± 2.8 SD) were compared to 54 healthy knees (27 individuals, 14.9 years ± 2.4 SD). Peak hip, knee and pelvis kinematics and kinetics were captured using 3D-gait analysis (VICON, 12 cameras, 200 Hz, Plug-in-Gait, two force plates) and compared between the two groups. One cycle (100%) consisted of 51 data points. The mean of six trials was computed.

RESULTS

Peak hip adduction angles and abduction moments were significantly higher in patients with recurrent patellar dislocation compared to the control group (p < 0.001 and 0.002, respectively). Peak internal hip rotation did not differ significantly.

CONCLUSION

Elevated hip adduction angles and higher hip abduction moments in gait of adolescents with recurrent patellar dislocation may indicate an impaired function of hip abductors that contributes to patellar instability.

A Time-Division Position-Sensitive Detector Image System for High-Speed Multitarget Trajectory Tracking

High-speed trajectory tracking with real-time processing capability is particularly important in the fields of pilotless automobiles, guidance systems, robotics, and filmmaking. The conventional optical approach to high-speed trajectory tracking involves charge coupled device (CCD) or complementary metal-oxide-semiconductor (CMOS) image sensors, which suffer from trade-offs between resolution and framerates, complexity of the system, and enormous data-analysis processes. Here, a high-speed trajectory tracking system is designed by using a time-division position-sensitive detector (TD-PSD) based on a graphene-silicon Schottky heterojunction. Benefiting from the high-speed optoelectronic response and sub-micrometer positional accuracy of the TD-PSD, multitarget real-time trajectory tracking is realized, with a maximum image output framerate of up to 62 000 frames per second. Moreover, multichannel trajectory tracking and image-distortion correction functionalities are realized by TD-PSD systems through frequency-related image preprocessing, which significantly improves the capacity of real-time information processing and image quality in complicated light environments.