The aim of this study was to analyse sex-specific differences contributing to dynamic valgus in competitive soccer players before and after a standardised fatiguing protocol.

Thirty-nine healthy female and male competitive soccer players (19 females and 20 males) were recruited for the purpose of this study. Bilateral medial knee displacement (MKD) was assessed during drop jump landings using a three-dimensional motion capture system before and after a standardised fatiguing protocol. In addition, all soccer players underwent clinical examinations, including rotational hip range of motion (ROM), isokinetic strength testing and magnetic resonance imaging (MRI) of the hip and knee. Sex-specific and fatigue-dependent differences were reported, and the influence of demographic, clinical and radiographic factors on MKD was analysed via multiple linear regression models.

Compared with male soccer players, female soccer players demonstrated a tendency towards increased MKD during drop jump landings before (p = 0.09) and after the fatiguing protocol (p = 0.04). Sex-specific differences included increased hip internal rotation (IR) ROM, decreased hip external rotation (ER) strength and increased femoral torsion in females (all p < 0.002). According to the multiple linear regression models (stepwise method), increased hip IR ROM (90° of flexion) and the non-dominant leg remained the sole independent predictors of increased MKD during drop jump landings before (p < 0.01 and p = 0.02, respectively) and after fatigue (p < 0.01 and p < 0.01, respectively). An increase in hip IR ROM in females was linearly related to MKD after fatigue (R2 = 0.25; p < 0.01).

Female soccer players exhibited increased dynamic valgus before and after fatigue, which is likely attributed to joint mobility, as well as muscular and anatomical differences, such as increased hip IR ROM, reduced hip ER strength and increased femoral torsion. In particular, females with increased hip IR ROM were more susceptible to effects of fatigue on MKD, which may increase their risk for anterior cruciate ligament injury.

Level III.

The joint position reproduction (JPR) approach is commonly used to assess joint position sense (JPS), but its psychometric properties in children remain unexplored. This study aimed to assess the reliability and precision of a multi-joint JPR protocol for assessing lower-limb JPS in typically developing (TD) children. Ankle, knee, and hip JPS were assessed in TD children (aged 5-12 years), on two different days, by a single rater using a standardized JPR protocol. The mean and best error (joint reproduction error, °) between the target and reproduction angle were calculated from three-dimensional kinematics for each joint across three trials. Total, joint, and limb JRE scores were provided. For JPR reliability, the intraclass correlation coefficient (ICC, 2.1) was reported. For JPR precision, the standard error of measurement (SEM) and smallest detectable difference (SDD) were calculated. Across 270 JPR trials (15 children, 8.6 ± 1.2 years, 8 boys), the mean and best JRE were 3.7° and 2.5°, respectively. The ICC ranged from poor to fair (0.01-0.44) for mean JRE, and fair to very good (0.46-0.77) for best JRE. The SEM ranged from 0.8° to 1.8°. The SDD was less than 5°, ranging from 2.3° to 4.5°. Evaluating ankle, knee, and hip JPS in children using passive JPR is more reliable and precise when using the best JRE. This study highlights the need for a multi-joint JPR approach and provide joint- and limb-specific SEM and SDD values.

BackgroundPoor scapular resting position and abnormal motion with the lack of proper muscle performance contribute to the development of shoulder dysfunction and pain. Various taping methods was proven to stabilize the scapula in a retracted position and facilitate proper scapular motion.ObjectivesTo compare the effects of mechanical correction of kinesiology tape (KT) and mulligan tape (MuT) methods on electromyographic activity (EMG) and kinematics of scapulothoracic (ST) and kinetics of glenohumeral (GH) joints in computer users affected with scapular dyskinesis (SD).MethodsThis study is a single-blinded randomized placebo-controlled clinical trial study with convenience sampling. Thirty-six male computer users with SD were randomized in three groups of KT, MuT, and placebo tape (PT). A two-session evaluation, in each session two times, with a 72-h interval was done. The outcome measures of the EMG were peak root mean square (PRMS) and RMS activity of upper trapezius (UT), middle trapezius (MT), lower trapezius (LT), deltoid (Del), and serratus anterior (SA) muscles during typing and 120° of scaption tasks. Anterior tipping, upward rotation, and internal rotation of the scapula were also recorded using a motion capture system and processed using custom code written in Matlab (R2015b; Mathworks, Inc., Natick, MA).ResultsIn MuT, PRMS and RMS of UT and MT; PRMS of SA in 120° scaption; and RMS of MT in typing position increased significantly (p < 0.05). In KT, SA RMS in 120° scaption increased and internal and upward rotation of scapula in typing position decreased significantly (p < 0.05).ConclusionMulligan tape showed a better effect on increasing EMG activity of the muscles which have a controlling role in SD correction and KT had a better impact on decreasing scapula internal rotation which is typically impaired in SD.

Vojta therapy (VT) enhances postural control and improves gait abilities. However, there is limited evidence regarding the impact of home-based VT on individuals with Down syndrome (DS).

This study aimed to assess the feasibility and preliminary effects of a two-week home-based VT program on spatiotemporal gait parameters in individuals with DS.

Sixteen individuals with DS (mean age = 17.88 ± 4.57 years, 8 females) participated in a two-week home-based VT program. Feasibility was measured through adherence rates and the occurrence of adverse events. Spatiotemporal gait parameters were evaluated before and after the intervention using the Vicon motion capture system.

All participants (100%) successfully completed the home-based VT program with no reported adverse events. Significant improvements were observed in walking speed, cadence, step time (left and right), stride time (left and right), step length (left and right), stride length (left and right), and single support (left and right) (p < 0.05).

This preliminary study suggests that home-based VT is a feasible approach and can lead to meaningful improvements in spatiotemporal gait parameters for individuals with DS. Further research with larger sample sizes, more robust designs, and extended follow-up periods is recommended.

Posture of the upper neck is considered by some to contribute to neck pain and headache. Infrared reflectors and cameras permit non-invasive three-dimensional (3D) evaluation of head and neck range of motion but have not been used to examine the relative pose (position and orientation) of the head, upper and lower neck.

Can the relative 3D pose of the head, upper and lower neck regions of adult humans be non-invasively measured and perturbated while recording the characteristics of neck or head pain?

An optical motion capture system was used in a repeat measure descriptive analysis study. Continuous recordings of the 3D position of fiducial markers affixed to the head (Hf), skin over C2 spinous process (C2f) and vertebral prominence (VPf) of adult (2 males 1 female, 27-61-year-old) volunteers free of pain were made while seated at a desktop computer that allowed recording of the characteristics of ensuing pain. Control trials involved 20 minutes of video viewing. Test trials included occlusion of upper third of visual field during the trial's second phase. Trial allocation was random, repeat trials were > 5 days apart.

Median angles between Hf, C2f and VPf in control trials changed little (median 1 degree; range 0-8 degrees). Single case study effect size measure PEM-Ta, percentage of test phase observations above chance compared to the control phase trend, ranged from 13 % to 100 % (median 100 %). Test phase trial median angles between fiducial markers primarily involved Y axis (Pitch) rotations (range C2f to Hf 5-14; VPf to Hf 12-29 degrees; effect sizes 98-100 %, except one trial, 21 %) with little change about other axes.

This study provides preliminary evidence that the relative 3D pose of the head, upper and lower neck of seated adults can be non-invasively measured and perturbated while simultaneously characterising ensuing pain.

Ensuring the accurate tracking of hand and fingers movements is an ongoing challenge for upper limb rehabilitation assessment, as the high number of degrees of freedom and segments in the limited volume of the hand makes this a difficult task. The objective of this study is to evaluate the performance of two markerless approaches (the Leap Motion Controller and the Google MediaPipe API) in comparison to a marker-based one, and to improve the precision of the markerless methods by introducing additional data processing algorithms fusing multiple recording devices. Fifteen healthy participants were instructed to perform five distinct hand movements while being recorded by the three motion capture methods simultaneously. The captured movement data from each device was analyzed using a skeletal model of the hand through the inverse kinematics method of the OpenSim software. Finally, the root mean square errors of the angles formed by each finger segment were calculated for the markerless and marker-based motion capture methods to compare their accuracy. Our results indicate that the MediaPipe-based setup is more accurate than the Leap Motion Controller-based one (average root mean square error of 10.9° versus 14.7°), showing promising results for the use of markerless-based methods in clinical applications.

This study aimed to evaluate the clinical and functional outcomes of autologous bone grafting with spheroid-based matrix-induced autologous chondrocyte implantation (MABCI) for osteochondral defects of the knee by analysing pre- and postoperative patient-reported outcome measures (PROMs). Postoperative gait analysis was conducted and compared with a matched healthy control group to investigate biomechanical deviations.

A total of 35 patients (m: 21, f: 14; mean defect size: 4.2 ± 2.4 cm², localisation: femoral condyle: 31, patellofemoral: 5) were analysed. The mean follow-up was 42.6 ± 22.8 months. International Knee Documentation Committee (IKDC), Knee Injury and Osteoarthritis Outcome Score (KOOS), PROMIS 29 profile, and a questionnaire on patient perception of treatment success were assessed to evaluate PROMs. 3D-instrumented gait analysis (GRAIL, Motek) was used to assess lower extremity kinematics, kinetics and vertical ground reaction forces, compared to sex-, age- and body mass index-matched healthy controls.

All clinical scores showed significant improvement compared to the preoperative condition (IKDC: 73.1 ± 10.1 vs. 56.6 ± 17.2, p < 0.01; KOOS subcategories: pain 82.0 [±12.7] vs. 70.7 [±16.7] [p < 0.01], symptoms 79.1 [±20.3] vs. 68.9 [±13.9] [p < 0.01], activities of daily living 90.1 [±11.2] vs. 80.5 [±15.6] [p < 0.01], sport and recreational function: 65.3 [±19.3] vs. 51.3 [±26.29] [p < 0.01], quality of life 52.2 [±18.6] vs. 42.6 [±18.6] [p < 0.01]; numeric pain rating scale: 2.7 ± 2.0 vs. 5.0 ± 2.5, p < 0.01). The analysed patients reported a high satisfaction rate (94.3%). Self-selected walking speed was significantly lower than in healthy controls (1.17 ± 0.17 m/s vs. 0.98 ± 0.18 m/s, p < 0.01). Peak knee flexion angle (PKA) during loading response was significantly smaller (9.6° ± 7.0 vs. 17.7° ± 4.6, p < 0.01), and knee extension moment was significantly reduced (0.1 Nm/kg ± 0.2 vs. 0.4 Nm/kg ± 0.2, p < 0.01).

MABCI is an effective treatment for osteochondral knee defects, showing significant improvements in all evaluated PROMs. Postoperative gait analysis revealed abnormal gait patterns, including reduced PKA and lower knee extension moment, suggesting a need for further rehabilitation to optimise functional recovery.

Level III.

Walking on compliant terrains, like carpets, grass, and soil, presents a unique challenge, especially for individuals with mobility impairments. In contrast to rigid-ground walking, compliant surfaces alter movement dynamics and increase the risk of falls. Understanding and modeling gait control across such soft and deformable surfaces is thus crucial for maintaining daily mobility. However, access to the necessary equipment for modeling compliant surface walking is limited. Therefore, in this paper, we present the first publicly available biomechanics dataset of 20 individuals walking on terrains of varying compliance, using a unique robotic device, the Variable Stiffness Treadmill 2 (VST 2), designed to simulate walking on adjustable compliant terrain. VST 2 provides a consistent and reproducible environment for studying the biomechanics of walking on such surfaces within laboratory settings. The goal of this dataset is to provide insights into the muscular, kinematic, and kinetic adaptations that occur when humans walk on compliant terrain in order to design better controllers for prosthetic limbs, improve rehabilitation protocols, and develop adaptive assistive devices that can enhance mobility on compliant surfaces.

Estimating how the human body moves in space and time-body kinematics-has important applications for industry, healthcare, and several research fields. Gold-standard methodologies capturing body kinematics are expensive and impractical for naturalistic recordings as they rely on infrared-reflective wearables and bulky instrumentation. To overcome these limitations, several algorithms have been developed to extract body kinematics from plain video recordings. This comes with a drop in accuracy, which however has not been clearly quantified. To fill this knowledge gap, we analysed a dataset comprising 46 human participants exhibiting spontaneous movements of varying amplitude. Body kinematics were estimated using OpenPose (video-based) and Vicon (infrared-based) motion capture systems simultaneously. OpenPose accuracy was assessed using Vicon estimates as ground truth. We report that OpenPose accuracy is overall moderate and varies substantially across participants and body parts. This is explained by variability in movement amplitude. OpenPose estimates are weak for low-amplitude movements. Conversely, large-amplitude movements (i.e., > ~ 10 cm) yield highly accurate estimates. The relationship between accuracy and movement amplitude is not linear (but mostly exponential or power) and relatively robust to camera-body distance. Together, these results dissect the limits of video-based motion capture and provide useful guidelines for future studies.

In rotator cuff tears, scapular dyskinesis is often observed. The aim of our study is to better understand the cause and the role of scapular dyskinesis in rotator cuff tears and evaluate changes in scapulothoracic kinematics after Lidocaine subacromial injection and surgery in patients with medium-sized (1-3 cm) rotator cuff tear.

The scapular motion during humerus sagittal flexion of nine healthy persons (healthy group, HG) and nine persons with a medium-sized rotator cuff tear (surgery group, SG) was investigated using the VICON motion capture system and upper limb evaluation in movement analysis software. In addition, quality of life and functional outcomes were assessed in the SG group using American Shoulder and Elbow Surgeons, Oxford and Constant-Murley scores and rotator muscle force and Visual Analogue Scale score were evaluated. The SG was further divided into three subgroups: measurements were performed preoperatively (before surgery native subgroup-BSN), then after subacromial Lidocaine injection (before surgery injection subgroup-BSI) and 6 months after rotator cuff reconstruction (after surgery subgroup-AS). Changes observed after injection (BSI) and surgery (AS) were compared to the BSN.

In the BSI, a significant reduction (p < .025) in protraction was observed in the raising phase between 20° and 70° comparing it to the BSN, protraction decreased by 5.3° ± 7.9° (mean ± standard deviation [SD]). In the lowering phase between 80° and 30°, we registered a decrease of protraction by 6.0° ± 8.3° (mean ± SD). In the AS, we observed an approximation of protraction to the HG, but no significant change was detected.

Significant reduction in scapular protraction was demonstrated with Lidocaine subacromial injection during both the arm raising and lowering phases. Six months of rehabilitation treatment in the postoperative period is not enough to fully eliminate scapular dyskinesis.

Level II.

Objective physical function assessment is crucial for determining patient eligibility for treatment and adjusting the treatment intensity. Existing assessments, such as performance status, are not well standardized, despite their frequent use in daily clinical practice. This paper explored how artificial intelligence (AI) could predict physical function scores from various patient data sources and reviewed methods to measure objective physical function using this technology. This review included relevant articles published in English that were retrieved from PubMed. These studies utilized AI technology to predict physical function indices from patient data extracted from videos, sensors, or electronic health records, thereby eliminating manual measurements. Studies that used AI technology solely to automate traditional evaluations were excluded. These technologies are recommended for future clinical systems that perform repeated objective physical function assessments in all patients without requiring extra time, personnel, or resources. This enables the detection of minimal changes in a patient's condition, enabling early intervention and enhanced outcomes.

Gait analysis is essential for evaluating locomotor function and fall risk, particularly in the elderly and in various musculoskeletal disorders. Traditional gait analysis systems face challenges such as technical difficulties, high cost, and complexity of use. Therefore, there is a need for a more accessible and cost-effective system with a wider clinical applicability.

This study aimed to validate the newly developed IB-gait® system (InBody, Republic of Korea), a camera-based gait analysis tool, by comparing it against the VICON system.

A total of 28 community-dwelling adults without gait abnormalities (mean age 24.9 years) were enrolled in this study. The participants underwent gait analysis at their self-selected speed using VICON and IB-gait® simultaneously. Nine spatiotemporal gait parameters, including stride length (m), step length (m), stride duration (s), double-limb duration (s), stance phase (s), swing phase (s), cadence (velocity × 120/stride length), and gait velocity (m/s) were measured. The agreement between the two systems was tested using Bland-Altman plots and intraclass correlation coefficients (ICC).

The IB-gait® showed a high degree of agreement with the VICON system in most gait parameters. The ICC showed excellent reliability for stride length (0.97), step length (0.92), gait velocity (0.97), cadence (0.97), and stride duration (0.79). However, it showed lower reliability in time-based parameters, including double-limb duration (0.12), stance phase (0.54), swing phase (0.241), and stance/swing phase ratio (0.11).

The IB-gait® system appears to be a feasible and cost-effective alternative to VICON system for gait analysis, particularly showing a high level of agreement in the distance-based parameters. Its practicality in clinical settings makes it a valuable tool for widespread use in gait analysis. However, further refinement of time-based parameter measurements and validation in diverse patient populations are needed to enhance its applicability.

Musculoskeletal injuries (MSKIs) among active duty soldiers result in more than 10 million limited duty days each year and account for more than 70% of the medically nondeployable population. Overuse injuries in lower limbs from running, foot marching long distances with heavy loads, and lifting heavy objects are the most common types of injuries in the military. Physical training and rehabilitation exercises for greater resiliency through aerobic, muscle strength, endurance, and agility conditioning programs can prevent or reduce the effects of MSKIs if Soldiers adhere to proper biomechanics and training techniques. We are introducing a three-dimensional (3D) camera-based platform for Optical Screening and Conditioning for Injury Resilience (OSCIR) that is designed to identify and correct high-risk movement patterns based on quantifiable biomechanical measurements in clinical or field settings. Our goal is to improve resilience to MSKI by offering greater access to quality of movement skills in warfighters through an autonomous device that can be used in Sports Medicine and Reconditioning Team (SMART) clinics and High-Intensity Tactical Training (HITT) sites.

OSCIR fuses four pairs of Kinect Azure cameras into a concise footprint to achieve suitable sampling rates and an unobstructed field of view for accurate dynamic movement tracking using a custom point cloud solution. We designed a unique multistage 3D joint tracking algorithm architecture to methodically isolate the human body point cloud from the background, identify individual limb segments, and perform iterative joint optimization at the global and local joint levels. We evaluated the feasibility of our prototype system among N = 12 control participants (6 M/6 F; 21-37 years) in compliance with the Western Institutional Review Board (Tracking #20225920, approved on November 4, 2022). Five task-specific MSKI outcome metrics identified by end-user physical therapists and athletic trainers as indicators for movement quality were assessed across 7 lower-extremity exercises derived from standardized MSK assessment/conditioning batteries used in the military. Data were recorded concurrently by OSCIR and a reference standard Vicon motion capture system for validating system accuracy.

Task-specific MSKI indicators for knee flexion and hip flexion range of motion achieved an average error of 4.05 ± 2.34°, while 3D position-based postural outcomes of left-right foot distance, left-right hand distance, and step length obtained mean absolute errors of 2.58 ± 2.30 cm. Results support the feasibility of our system in achieving outcomes that are comparable to currently accepted laboratory standards.

Our study describes the integration process for a 3D camera-based clinical system for MSKI conditioning and rehabilitation. The impact of our system will enable key stakeholders in the military to manage MSKIs in warfighters by automating key assessment and rehabilitation test batteries; making tests more readily accessible, and interpretations more accurate by providing objective biomechanical measures. OSCIR is undergoing turn-key design features to serve as a screening tool for warfighters to readily assess susceptibility to MSKI or as a training platform to help guide exercise techniques to achieve resiliency against future injuries.

This study validated the accuracy of the acromion marker cluster (AMC) and scapula spinal marker cluster (SSMC) methods compared with upright four-dimensional computed tomography (4DCT) analysis.

Sixteen shoulders of eight healthy males underwent AMC and SSMC assessments. Active shoulder elevation was tracked using upright 4DCT and optical motion capture system. The scapulothoracic and glenohumeral rotation angles calculated from AMC and SSMC were compared with 4DCT. Additionally, the motion of these marker clusters on the skin with shoulder elevation was evaluated.

The average differences between AMC and 4DCT during 10°-140° of humerothoracic elevation were - 2.2° ± 7.5° in scapulothoracic upward rotation, 14.0° ± 7.4° in internal rotation, 6.5° ± 7.5° in posterior tilting, 3.7° ± 8.1° in glenohumeral elevation, - 8.3° ± 10.7° in external rotation, and - 8.6° ± 8.9° in anterior plane of elevation. The difference between AMC and 4DCT was significant at 120° of humerothoracic elevation in scapulothoracic upward rotation, 50° in internal rotation, 90° in posterior tilting, 120° in glenohumeral elevation, 100° in external rotation, and 100° in anterior plane of elevation. However, the average differences between SSMC and 4DCT were - 7.5 ± 7.7° in scapulothoracic upward rotation, 2.0° ± 7.0° in internal rotation, 2.3° ± 7.2° in posterior tilting, 8.8° ± 7.9° in glenohumeral elevation, 2.0° ± 9.1° in external rotation, and 1.9° ± 10.1° in anterior plane of elevation. The difference between SSMC and 4DCT was significant at 50° of humerothoracic elevation in scapulothoracic upward rotation and 60° in glenohumeral elevation, with no significant differences observed in other rotations. Skin motion was significantly smaller in AMC (28.7 ± 4.0 mm) than SSMC (38.6 ± 5.8 mm). Although there was smaller skin motion in AMC, SSMC exhibited smaller differences in scapulothoracic internal rotation, posterior tilting, glenohumeral external rotation, and anterior plane of elevation compared to 4DCT.

This study demonstrates that AMC is more accurate for assessing scapulothoracic upward rotation and glenohumeral elevation, while SSMC is preferable for evaluating scapulothoracic internal rotation, posterior tilting, glenohumeral external rotation, and anterior plane of elevation, with smaller differences compared to 4DCT.

Velocity-based training (VBT) is commonly used for programming and autoregulation of resistance training. Velocity may also be measured during resistance training to estimate one repetition maximum and monitor fatigue. This study quantifies the validity of Metric VBT, a mobile application that uses camera-vision for measuring barbell range of motion (RoM) and mean velocity during resistance exercises.

Twenty-four participants completed back squat and bench press repetitions across various loads. Five mobile devices were placed at varying angles (0, ±10, and ±20°) perpendicular to the participant. The validity of Metric VBT was assessed in comparison to Vicon motion analysis using precision and recall, Lin's concordance correlation coefficient, and Bland-Altman plots. Proportional bias was assessed using linear regression.

Metric VBT accurately detected over 95% of repetitions. It showed moderate to substantial agreement with the Vicon system for measuring RoM in both exercises. The average Limits of Agreement (LoA) for RoM across all camera positions were -5.45 to 4.94 cm for squats and -5.80 to 3.55 cm for bench presses. Metric VBT exhibited poor to moderate agreement with the Vicon system for measuring mean velocity. The average LoA for mean velocity were 0.03 to 0.25 m/s for squats and -5.80 to 3.55 m/s for bench presses. A proportional bias was observed, with bias increasing as repetition velocity increased.

Metric VBT's wide LoA for measuring RoM and mean velocity highlights significant accuracy concerns, exceeding acceptable levels for practical use. However, for users prioritizing repetition counts over precise RoM or mean velocity data, the application can still provide useful information for monitoring workout volume.

This paper introduces a method for measuring wing motion, deformation, and inertial forces in bio-inspired aircraft research using a camera motion capture system. The method involves placing markers on the wing surface and fitting rigid planes to determine the wing's spatial axis. This allows for describing the wing's rigid motion and obtaining deformation characteristics, such as deflection, twist angle, and gap distance of the forewing and hindwing. An image-based method is proposed for determining wing mass distribution, mass blocks, and mass points for inertial force measurement. The study addresses wing motion, deformation, and inertial force measurement in a real butterfly-like flapping wing vehicle and demonstrates the effectiveness of the approach. The results reveal that inertial forces play a negligible role in the generation of lift peaks and contribute minimal lift during the entire flapping cycle. Furthermore, a transitional phase between downstroke and upstroke is found in flexible wing motion, which has high lift production. This measurement approach offers a rapid and effective solution to experimental challenges in bio-inspired aircraft design and optimization.

Two-dimensional (2D) video is a common tool used during sports training and competition to analyze movement. In these videos, biomechanists determine key events, annotate joint centers, and calculate spatial, temporal, and kinematic parameters to provide performance reports to coaches and athletes. Automatic tools relying on computer vision and artificial intelligence methods hold promise to reduce the need for time-consuming manual methods.

This study systematically analyzed the steps required to automate the video analysis workflow by investigating the applicability of a threshold-based event detection algorithm developed for 3D marker trajectories to 2D video data at four sampling rates; the agreement of 2D keypoints estimated by an off-the-shelf pose estimation model compared with gold-standard 3D marker trajectories projected to camera's field of view; and the influence of an offset in event detection on contact time and the sagittal knee joint angle at the key critical events of touch down and foot flat.

Repeated measures limits of agreement were used to compare parameters determined by markerless and marker-based motion capture.

Results highlighted that a minimum video sampling rate of 100 Hz is required to detect key events, and the limited applicability of 3D marker trajectory-based event detection algorithms when using 2D video. Although detected keypoints showed good agreement with the gold-standard, misidentification of key events-such as touch down by 20 ms resulted in knee compression angle differences of up to 20°.

These findings emphasize the need for de novo accurate key event detection algorithms to automate 2D video analysis pipelines.

Movement variability tracking traces the spatiotemporal movement of limbs against a pre-recorded action template. This paper introduces an ultra-low-power, low footprint, and data-efficient movement variability detection algorithm implemented on-chip on an inertial sensor die. During the training phase, the user attaches an inertial sensor to the target limb and performs limb movements under supervision. The algorithm within the sensor automatically segments the region of interest with maximal entropic density and generates approximate gravity vector templates of the action primitive. During the inference phase, weighted similarity metrics provide the latent geometric distance between temporal portions of the stored templates and live template as heatmaps. These heatmaps provide quantitative and actionable information on which parts of the movement trajectory to correct. The algorithm requires under 6 seconds of training data, under 7 kB of memory and 0.2 mA of current on-sensor, and has a temporal resolution of 0.5 seconds. The concept benefits a broad application spectrum, including sports analysis, exercise monitoring, rehabilitation, and gait tracking.

Muscular dystrophies (MD) are a group of genetic neuromuscular disorders that cause progressive weakness and loss of muscles over time, influencing 1 in 3500-5000 children worldwide. New and exciting treatment options have led to a critical need for a clinical post-marketing surveillance tool to confirm the efficacy and safety of these treatments after individuals receive them in a commercial setting. For MDs, functional gait assessment is a common approach to evaluate the efficacy of the treatments because muscle weakness is reflected in individuals' walking patterns. However, there is little incentive for the family to continue to travel for such assessments due to the lack of access to specialty centers. While various existing sensing devices, such as cameras, force plates, and wearables can assess gait at home, they are limited by privacy concerns, area of coverage, and discomfort in carrying devices, which is not practical for long-term, continuous monitoring in daily settings. In this study, we introduce a novel functional gait assessment system using ambient floor vibrations, which is non-invasive and scalable, requiring only low-cost and sparsely deployed geophone sensors attached to the floor surface, suitable for in-home usage. Our system captures floor vibrations generated by footsteps from patients while they walk around and analyzes such vibrations to extract essential gait health information. To enhance interpretability and reliability under various sensing scenarios, we translate the signal patterns of floor vibration to pathological gait patterns related to MD, and develop a hierarchical learning algorithm that aggregates insights from individual footsteps to estimate a person's overall gait performance. When evaluated through real-world experiments with 36 subjects (including 15 patients with MD), our floor vibration sensing system achieves a 94.8% accuracy in predicting functional gait stages for patients with MD. Our approach enables accurate, accessible, and scalable functional gait assessment, bringing MD progressive tracking into real life.

A skin marker-based motion capture model providing measures of scapular rotations was recently developed. The aim of this study was to investigate the concurrent validity and the interrater reliability of the model. Shoulder range of motion (RoM) and activities of daily living (ADL) were tested in healthy volunteers with reflective markers on the scapula and thorax. To investigate the validity, the model was compared to simultaneous data collection from markers on a scapular intracortical pin. The interrater reliability was tested by comparing the skin marker-based protocol performed by two investigators. The mean root mean square error (RMSE) and the intraclass correlation coefficient (ICC(2,1)) were calculated to determine the validity and the interrater reliability, respectively. Eight subjects were included in the validity test: female/male = 2/6, mean (SD) age 35.0 (3.0) and BMI 23.4 (3.3). The mean RMSE of all scapular rotations ranged 2.3-6.7° during shoulder RoM and 2.4-7.6° during ADL. The highest errors were seen during sagittal and scapular plane flexions, hair combing and eating. The reliability test included twenty subjects: female/male = 8/12, mean (SD) age 31.4 (4.9) and BMI 22.9 (1.7). The ICC(2,1) for measuring protraction ranged 0.07-0.60 during RoM and 0.27-0.69 for ADL, for upward rotation the corresponding ICC(2,1) ranged 0.01-0.64 and 0.38-0.60, and anterior tilt 0.25-0.83 and 0.25-0.62. The validity and interrater reliability of the model are task dependent, and interpretation should be made with caution. The model provides quantitative measurements for objective assessment of scapular movements and can potentially supplement the clinical examination in certain motion tasks.

Robust hand motion tracking holds promise for improved human-machine interaction in diverse fields, including virtual reality, and automated sign language translation. However, current wearable hand motion tracking approaches are typically limited in detection performance, wearability, and durability. This article presents a hand motion tracking system using multiple soft polymer acoustic waveguides (SPAWs). The innovative use of SPAWs as strain sensors offers several advantages that address the limitations. SPAWs are easily manufactured by casting a soft polymer shaped as a soft acoustic waveguide and containing a commercially available small ceramic piezoelectric transducer. When used as strain sensors, SPAWs demonstrate high stretchability (up to 100%), high linearity (R2 > 0.996 in all quasi-static, dynamic, and durability tensile tests), negligible hysteresis (<0.7410% under strain of up to 100%), excellent repeatability, and outstanding durability (up to 100,000 cycles). SPAWs also show high accuracy for continuous finger angle estimation (average root-mean-square errors [RMSE] <2.00°) at various flexion-extension speeds. Finally, a hand-tracking system is designed based on a SPAW array. An example application is developed to demonstrate the performance of SPAWs in real-time hand motion tracking in a three-dimensional (3D) virtual environment. To our knowledge, the system detailed in this article is the first to use soft acoustic waveguides to capture human motion. This work is part of an ongoing effort to develop soft sensors using both time and frequency domains, with the goal of extracting decoupled signals from simple sensing structures. As such, it represents a novel and promising path toward soft, simple, and wearable multimodal sensors.

In the field of behavioral neuroscience, the classification and scoring of animal behavior play pivotal roles in the quantification and interpretation of complex behaviors displayed by animals. Traditional methods have relied on video examination by investigators, which is labor-intensive and susceptible to bias. To address these challenges, research efforts have focused on computational methods and image-processing algorithms for automated behavioral classification. Two primary approaches have emerged: marker- and markerless-based tracking systems. In this study, we showcase the utility of "Augmented Reality University of Cordoba" (ArUco) markers as a marker-based tracking approach for assessing rat engagement during a nose-poking go/no-go behavioral task. In addition, we introduce a two-state engagement model based on ArUco marker tracking data that can be analyzed with a rectangular kernel convolution to identify critical transition points between states of engagement and distraction. In this study, we hypothesized that ArUco markers could be utilized to accurately estimate animal engagement in a nose-poking go/no-go behavioral task, enabling the computation of optimal task durations for behavioral testing. Here, we present the performance of our ArUco tracking program, demonstrating a classification accuracy of 98% that was validated against the manual curation of video data. Furthermore, our convolution analysis revealed that, on average, our animals became disengaged with the behavioral task at ∼75 min, providing a quantitative basis for limiting experimental session durations. Overall, our approach offers a scalable, efficient, and accessible solution for automated scoring of rodent engagement during behavioral data collection.

Research using animal models suggests that intensive motor skill training in infants under 2 years old with cerebral palsy (CP) may significantly reduce, or even prevent, maladaptive neuroplastic changes following brain injury. However, the effects of such interventions to tentatively prevent secondary neurological damages have never been assessed in infants with CP. This study aims to determine the effect of the baby Hand and Arm Bimanual Intensive Therapy Including Lower Extremities (baby HABIT-ILE) in infants with unilateral CP, compared with a control intervention.

This randomised controlled trial will include 48 infants with unilateral CP aged (corrected if preterm) 6-18 months at the first assessment. They will be paired by age and by aetiology of the CP, and randomised into two groups (immediate and delayed). Assessments will be performed at baseline and at 1 month, 3 months and 6 months after baseline. The immediate group will receive 50 hours of baby HABIT-ILE intervention over 2 weeks, between first and second assessment, while the delayed group will continue their usual activities. This last group will receive baby HABIT-ILE intervention after the 3-month assessment. Primary outcome will be the Mini-Assisting Hand Assessment. Secondary outcomes will include behavioural assessments for gross and fine motricity, visual-cognitive-language abilities as well as MRI and kinematics measures. Moreover, parents will determine and score child-relevant goals and fill out questionnaires of participation, daily activities and mobility.

Full ethical approval has been obtained by the Comité d'éthique Hospitalo-Facultaire/Université catholique de Louvain, Brussels (2013/01MAR/069 B403201316810g). The recommendations of the ethical board and the Belgian law of 7 May 2004 concerning human experiments will be followed. Parents will sign a written informed consent ahead of participation. Findings will be published in peer-reviewed journals and conference presentations.

NCT04698395. Registered on the International Clinical Trials Registry Platform (ICTRP) on 2 December 2020 and NIH Clinical Trials Registry on 6 January 2021. URL of trial registry record: https://clinicaltrials.gov/ct2/show/NCT04698395?term=bleyenheuft&draw=1&rank=7.

Miniature blimps are lighter-than-air vehicles which have become an increasingly common unmanned aerial system research platform due to their extended endurance and collision tolerant design. The UNSW-C bio-inspired miniature blimp consists of a 0.5 m spherical mylar envelope filled with helium. Four fins placed along the equator provide control over the three translatory axes and yaw rotations. A gondola attached to the bottom of the blimp contains all the electronics and flight controller. Here, we focus on using the UNSW-C blimp as a platform to achieve autonomous flight in GPS-denied environments. The majority of unmanned flying systems rely on GPS or multi-camera motion capture systems for position and orientation estimation. However, such systems are expensive, difficult to set up and not compact enough to be deployed in real environments. Instead, we seek to achieve basic flight autonomy for the blimp using a low-priced and portable solution. We make use of a low-cost embedded neural network stereoscopic camera (OAK-D-PoE) for detecting and positioning the blimp while an onboard inertia measurement unit was used for orientation estimation. Flight tests and analysis of trajectories revealed that 3D position hold as well as basic waypoint navigation could be achieved with variance (<0.1 m). This performance was comparable to that when a conventional multi-camera positioning system (VICON) was used for localizing the blimp. Our results highlight the potentially favorable tradeoffs offered by such low-cost positioning systems in extending the operational domain of unmanned flight systems when direct line of sight is available.

Low back pain is common in mountain biking due to the sustained flexion of the lumbar spine, particularly during fatiguing hill climbs. In this study, we investigated whether an ergonomic mountain bike saddle including a raised rear, a longitudinal dip, and a subtle lateral instability (the 'Active'-technology) can reduce acute low back pain at the end of a hill climb (>1 h) in a group of mountain bikers with a history of cycling-related low back pain (n = 28). In addition, we conducted a laboratory experiment to investigate the isolated effects of the 'Active'-technology on the cyclists' pelvis and spine motion as well as on the activity of surrounding muscles. The field test demonstrated a significant reduction in numerical low back pain ratings with the experimental saddle compared to the riders' own standard saddle (p = 0.001, strong effect). The laboratory-based data suggested that the 'Active'-technology does lead to potentially beneficial effects on pelvis-spine kinematics and muscle activity, which in combination with an optimised saddle geometry may explain the observed reduction in low back pain following mountain bike hill climbing.

The relationship between physical function, musculoskeletal disorders and sarcopenia is intricate. Current physical function tests, such as the gait speed test and the chair stand test, have limitations in eliminating subjective influences. To overcome this, smart devices utilizing inertial measurement unit sensors and artificial intelligence (AI)-based methods are being developed.

We employed cutting-edge technologies, including the smart insole device and pose estimation based on AI, along with three classification models: random forest (RF), support vector machine and artificial neural network, to classify control and sarcopenia groups. Patient data of 83 individuals were divided into train and test sets, with approximately 67% allocated for training. Classification models were implemented using RStudio, considering individual and combined variables obtained through pose estimation and smart insole measurements.

Performance evaluation of the classification models utilized accuracy, precision, recall and F1-score indicators. Using only pose estimation variables, accuracy ranged from 0.92 to 0.96, with F1-scores of 0.94-0.97. Key variables identified by the RF model were 'Hip_dif', 'Ankle_dif' and 'Hipankle_dif'. Combining variables from both methods increased accuracy to 0.80-1.00, with F1-scores of 0.73-1.00.

In our study, a classification model that integrates smart insole and pose estimation technology was assessed. The RF model showed impressive results, particularly in the case of the Hip and Ankle variables. The growth of advanced measurement technologies suggests a promising avenue for identifying and utilizing additional digital biomarkers in the management of various disorders. The convergence of AI technologies with diagnostics and treatment approaches a promising future for enhanced interventions in conditions like sarcopenia.

This reference dataset contains biomechanical data of 138 able-bodied adults (21-86 years) and 50 stroke survivors walking bare-footed at their preferred speed. It is unique due to its size, and population, including adults across the life-span and over 70 years, as well as stroke survivors. Full-body kinematics (PiG-model), kinetics and muscle activity of 14 back and lower limbs muscles was collected with a Vicon motion capture system, ground-embedded force plates, and a synchronized surface EMG system. The data is reliable to compare within and between groups as the same methodology and infrastructure were used to gather all data. Both source files (C3D) and post-processed ready-to-use stride-normalized kinematics, kinetics and EMG data (MAT-file, Excel file) are available, allowing high flexibility and accessibility of analysis for both researchers and clinicians. These records are valuable to examine ageing, typical and hemiplegic gait, while also offering a wide range of reference data which can be utilized for age-matched controls during normal walking.

The study investigated the feasibility of using action sport cameras for motion analysis research. Data acquired from two different marker-based motion capture systems and six different camera combinations were analyzed for motion reconstruction accuracy. Two different calibration procedures were used to determine the influence on marker position reconstruction. Static and dynamic calibration mean merit score differences between the reference and experimental camera systems were 0.4 mm and 1.3 mm, respectively. Angular displacement difference between the reference and experimental camera systems range between 0.1 and 2.0 degrees. A systematic bias (- 0.54 to 0.19 degrees) was determined between the reference and the experimental camera systems for range of motion. The mean of the multi-trial findings suggests the machine vision camera system calibrated with a dynamic procedure generated highly accurate three-dimensional reconstructed ROM data (0.5 degree) followed closely by the four action sport cameras implementing a static calibration procedure (0.5 degree). The overall findings suggest the selected machine vision and action sport camera systems produced comparable results to the reference motion analysis system. However, the combination of camera type, processing software, and calibration procedure can influence motion reconstruction accuracy.

Parkinson's disease (PD) is affecting about 1.2 million patients in Europe with a prevalence that is expected to have an exponential increment, in the next decades. This epidemiological evolution will be challenged by the low number of neurologists able to deliver expert care for PD. As PD is better recognized, there is an increasing demand from patients for rigorous control of their symptoms and for therapeutic education. In addition, the highly variable nature of symtoms between patients and the fluctuations within the same patient requires innovative tools to help doctors and patients monitor the disease in their usual living environment and adapt treatment in a more relevant way. Nowadays, there are various body-worn sensors (BWS) proposed to monitor parkinsonian clinical features, such as motor fluctuations, dyskinesia, tremor, bradykinesia, freezing of gait (FoG) or gait disturbances. BWS have been used as add-on tool for patients' management or research purpose. Here, we propose a practical anthology, summarizing the characteristics of the most used BWS for PD patients in Europe, focusing on their role as tools to improve treatment management. Consideration regarding the use of technology to monitor non-motor features is also included. BWS obviously offer new opportunities for improving management strategy in PD but their precise scope of use in daily routine care should be clarified.

This article proposes a virtual reality (VR) system for diagnosing and rehabilitating lower limb amputees. A virtual environment and an intelligent space are the basis of the proposed solution. The target audiences are physiotherapists and doctors, and the aim is to provide a VR-based system to allow visualization and analysis of gait parameters and conformity. The multi-camera system from the intelligent space acquires images from patients during gait. This way, it is possible to generate tridimensional information for the VR-based system. Among the provided functionalities, the user can explore the virtual environment and manage several features, such as gait reproduction and parameters displayed, using a head-mounted display and hand controllers. Besides, the system presents an automatic classifier that can assist physiotherapists and doctors in assessing abnormalities from conventional human gait. We evaluate the system through two quantitative experiments. The first one addresses the performance evaluation of the automatic classifier. The second analysis is through a Likert scale questionnaire submitted to a group of physiotherapists. In this case, the specialists evaluate the existing features of the proposed framework. The results from the questionnaire showed that the virtual environment is suitable for helping track patients' rehabilitation. Also, the neural network-based classifier results are promising, averaging higher than 91% for all evaluation metrics. Finally, a comparison with related works in the literature highlights the contributions of the proposed solution to the field.

For realistic and reliable full-body visualization in virtual reality, the HTC VIVE Tracker could be an alternative to highly complex and cost- and effort-intensive motion capture systems such as Vicon. Due to its lighter weight and smaller dimensions, the latest generation of trackers is proving to be very promising for capturing human movements. The aim of this study was to investigate the accuracy of the HTC VIVE Tracker 3.0 compared to the gold-standard Vicon for different arrangements of the base stations and various velocities during an athletic movement. Therefore, the position data from three trackers attached to the hip, knee and ankle of one sporty participant were recorded while riding a bicycle ergometer at different pedaling frequencies and different base station arrangements. As parameters for the measurement accuracy, the trajectories of the linear motion of the knee and the circular motion of the ankle were compared between VIVE and Vicon by calculating the spatial distance from the raw data at each point in time. Both the pedaling frequency and the arrangement of the base stations significantly affected the measurement accuracy, with the lowest pedaling frequency of 80 rpm and the rectangular arrangement recommended by the manufacturer showing the smallest spatial differences of 10.4 mm ± 4.5 mm at the knee and 11.3 mm ± 5.1 mm at the ankle. As the pedaling frequency increased gradually (120 rpm and 160 rpm), the measurement accuracy of the trackers per step decreased less at the knee (approximately 5 mm) than at the ankle (approximately 10 mm). In conclusion, the measurement accuracy for various athletic skills was high enough to enable the visualization of body limbs or the entire body using inverse kinematics in VR on the one hand and, on the other hand, to provide initial insights into the quality of certain techniques at lower speeds in sports science research. However, the VIVE trackers are not suitable for exact biomechanical analyses.

This work is focused on the preliminary stage of the 3D drone tracking challenge, namely the precise detection of drones on images obtained from a synchronized multi-camera system. The YOLOv5 deep network with different input resolutions is trained and tested on the basis of real, multimodal data containing synchronized video sequences and precise motion capture data as a ground truth reference. The bounding boxes are determined based on the 3D position and orientation of an asymmetric cross attached to the top of the tracked object with known translation to the object's center. The arms of the cross are identified by the markers registered by motion capture acquisition. Besides the classical mean average precision (mAP), a measure more adequate in the evaluation of detection performance in 3D tracking is proposed, namely the average distance between the centroids of matched references and detected drones, including false positive and false negative ratios. Moreover, the videos generated in the AirSim simulation platform were taken into account in both the training and testing stages.

Movement screens are widely used to identify aberrant movement patterns in hopes of decreasing risk of injury, identifying talent, and/or improving performance. Motion capture data can provide quantitative, objective feedback regarding movement patterns. The dataset contains three-dimensional (3D) motion capture data of 183 athletes performing mobility tests (ankle, back bend, crossover adduction, crossover rotation, elbows, head, hip turn, scorpion, shoulder abduction, shoulder azimuth, shoulder rotation, side bends, side lunges and trunk rotation) and stability tests (drop jump, hop down, L-cut, lunge, rotary stability, step down and T-balance) bilaterally (where applicable), the athletes' injury history, and demographics. All data were collected at 120 Hz or 480 Hz using an 8-camera Raptor-E motion capture system with 45 passive reflective markers. A total of 5,493 trials were pre-processed and included in .c3d and .mat formats. This dataset will enable researchers and end users to explore movement patterns of athletes of varying demographics from different sports and competition levels; develop objective movement assessment tools; and gain new insights into the relationships between movement patterns and injury.

Human walking reflects the state of human health. Numerous medical studies have been conducted to analyze walking patterns and to diagnose disease progression. However, this process requires expensive equipment and considerable time and manpower. Smartwatches are equipped with gyro sensors to detect human movements and graph-walking patterns. To measure the abnormality in walking using this graph, we developed a smartwatch gait coordination index (SGCI) and examined its usefulness. The phase coordination index was applied to analyze arm movements. Based on previous studies, the phase coordination index formula was applied to graphs obtained from arm movements, showing that arm and leg movements during walking are correlated with each other. To prove this, a smartwatch was worn on the arms and legs of 8 healthy adults and the difference in arm movements was measured. The SGCI values with abnormal walking patterns were compared with the SGCI values obtained during normal walking. In the first experiment, the measured leg SGCI in normal walking averaged 9.002 ± 3.872 and the arm SGCI averaged 9.847 ± 6.115. The movements of both arms and legs showed stable sinusoidal waves. In fact, as a result of performing a paired t test of both exercise phases measured by the strike point using the maximum and minimum values, it was confirmed that the 2 exercises were not statistically different, as it yielded a P value of 0.469 (significance level α = 0.05). The arm SGCI measured after applying the 3 kg weight impairment on 1 leg was 22.167 ± 4.705. It was confirmed that the leg SGCI and 3 kg weight arm SGCI were statistically significant, as it yielded a P value of 0.001 (significance level α = 0.05). The SCGI can be automatically and continuously measured with the gyro sensor of the smartwatch and can be used as an indirect indicator of human walking conditions.

Background: Toe clearance on stairs is typically measured using optoelectronic systems, though these are often constrained to the laboratory, due to their complex setups. Here we measured stair toe clearance through a novel prototype photogate setup and compared this to optoelectronic measurements. Methods: Twelve participants (age 22 ± 3 years) completed 25 stair ascent trials, each on a seven-step staircase. Toe clearance over the fifth step edge was measured using Vicon and the photogates. Twenty-two photogates were created in rows through laser diodes and phototransistors. The height of the lowest photogate broken at step-edge crossing was used to determine photogate toe clearance. A limits of agreement analysis and Pearson's correlation coefficient compared the accuracy, precision and relationship between systems. Results: We found a mean difference of -1.5 mm (accuracy) between the two measurement systems, with upper and lower limits (precision) of 10.7 mm and -13.8 mm, respectively. A strong positive correlation was also found (r = 70, n = 12, p = 0.009) between the systems. Discussion: The results suggest that photogates could be an option for measuring real-world stair toe clearances, where optoelectronic systems are not routinely used. Improvements to the design and measurement factors may help to improve the precision of the photogates.

The consolidation of telerehabilitation for the treatment of many diseases over the last decades is a consequence of its cost-effective results and its ability to offer access to rehabilitation in remote areas. Telerehabilitation operates over a distance, so vulnerable patients are never exposed to unnecessary risks. Despite its low cost, the need for a professional to assess therapeutic exercises and proper corporal movements online should also be mentioned. The focus of this paper is on a telerehabilitation system for patients suffering from Parkinson's disease in remote villages and other less accessible locations. A full-stack is presented using big data frameworks that facilitate communication between the patient and the occupational therapist, the recording of each session, and real-time skeleton identification using artificial intelligence techniques. Big data technologies are used to process the numerous videos that are generated during the course of treating simultaneous patients. Moreover, the skeleton of each patient can be estimated using deep neural networks for automated evaluation of corporal exercises, which is of immense help to the therapists in charge of the treatment programs.

Hockey skating objective assessment can help coaches detect players’ performance drop early and avoid fatigue-induced injuries. This study aimed to calculate and experimentally validate the 3D angles of lower limb joints of hockey skaters obtained by inertial measurement units and explore the effectiveness of the on-ice distinctive features measured using these wearable sensors in differentiating low- and high-calibre skaters. Twelve able-bodied individuals, six high-calibre and six low-calibre skaters, were recruited to skate forward on a synthetic ice surface. Five IMUs were placed on their dominant leg and pelvis. The 3D lower-limb joint angles were obtained by IMUs and experimentally validated against those obtained by a motion capture system with a maximum root mean square error of 5 deg. Additionally, among twelve joint angle-based distinctive features identified in other on-ice studies, only three were significantly different (p-value < 0.05) between high- and low-calibre skaters in this synthetic ice experiment. This study thus indicated that skating on synthetic ice alters the skating patterns such that the on-ice distinctive features can no longer differentiate between low- and high-calibre skating joint angles. This wearable technology has the potential to help skating coaches keep track of the players’ progress by assessing the skaters’ performance, wheresoever.

The primary aim of this laboratory-based human subject study was to evaluate the biomechanical loading associated with mining vehicles' multi-axial whole body vibration (WBV) by comparing joint torque and muscle activity in the neck and low back during three vibration conditions: mining vehicles' multi-axial, on-road vehicles' vertical-dominant, and no vibration. Moreover, the secondary aim was to determine the efficacy of a vertical passive air suspension and a prototype multi-axial active suspension seat in reducing WBV exposures and associated biomechanical loading measures. The peak joint torque and muscle activity in the neck and low back were higher when exposed to multi-axial vibration compared to the vertical-dominant or no vibration condition. When comparing the two suspension seats, there were limited differences in WBV, joint torque, and muscle activity. These results indicate that there is a need to develop more effective engineering controls to lower exposures to multi-axial WBV and related biomechanical loading. Practitioner Summary: This study found that mining vehicles' multi-axial WBV can increase biomechanical loading in the neck and back more so than on-road vehicles' vertical-dominant WBV. While a newly-developed multi-axial active suspension seat slightly reduced the overall WBV exposures, the results indicate that more effective engineering controls should be developed. Abbreviation: APDF: amplitude probability density function; Aw: weighted average vibration; BMI: body mass index; C7: The 7th cervical vertebra; EMG: electromyography; ES: erector spinae; IRB: institutional review board; ISO: International Organization for Standardization; L5/S1: the fifth lumbar vertebra (L5)/the first sacral vertebra(S1); MSDs: musculoskeletal disorders; MVC: maximum voluntary contraction; PSD: power spectral density; RVC: reference voluntary contraction; SCM: sternocleidomastoid; SD: standard deviation; SPL: splenius capitis; TRAP: trapezius; VDV: vibration dose value; WBV: whole body vibration.

Although it is evident that some patients with adolescent idiopathic scoliosis (AIS) have proprioceptive deficit in peripheral joints, knowledge on the proprioceptive function of the deformed spine is limited. Nonetheless, spinal proprioception in AIS may be affected three-dimensionally, prior studies only focussed on evaluating peripheral proprioception in single plane. Therefore, this study aimed to develop a novel spinal proprioception assessment using three-dimensional motion analysis in patients with AIS.

Participants were included if they had a primary diagnosis of AIS who did not receive or failed conservative treatments. Three trunk repositioning tests involving flexion-extension, lateral-flexion, and axial-rotation were conducted. A three-dimensional kinematics of the trunk was used as the outcome measures. The proprioceptive acuity was quantified by the repositioning error. The intra-examiner and test-retest reliability were analysed by the intraclass correlation coefficient (ICC).

Fifty-nine patients with AIS were recruited. Regarding the trunk flexion-extension test, the single measure ICC showed moderate reliability (0.46) and the average measures ICC demonstrated good reliability (0.72). As for the trunk lateral-flexion test, the reliability of single measure and average measures ICC was moderate (0.44) and good (0.70) reliability, respectively. For the trunk axial-rotation test, the single measure ICC indicated fair reliability (0.32), while the average measures ICC showed moderate reliability (0.59).

This is the first study to evaluate the reliability of novel three-dimensional spinal proprioception assessments in patients with AIS. The trunk flexion-extension repositioning test may be preferable clinical test given its highest reliability.

Autonomous systems usually require accurate localization methods for them to navigate safely in indoor environments. Most localization methods are expensive and difficult to set up. In this work, we built a low-cost and portable indoor location tracking system by using Raspberry Pi 4 computer, ultra-wideband (UWB) sensors, and inertial measurement unit(s) (IMU). We also developed the data logging software and the Kalman filter (KF) sensor fusion algorithm to process the data from a low-power UWB transceiver (Decawave, model DWM1001) module and IMU device (Bosch, model BNO055). Autonomous systems move with different velocities and accelerations, which requires its localization performance to be evaluated under diverse motion conditions. We built a dynamic testing platform to generate not only the ground truth trajectory but also the ground truth acceleration and velocity. In this way, our tracking system's localization performance can be evaluated under dynamic testing conditions. The novel contributions in this work are a low-cost, low-power, tracking system hardware-software design, and an experimental setup to observe the tracking system's localization performance under different dynamic testing conditions. The testing platform has a 1 m translation length and 80 μm of bidirectional repeatability. The tracking system's localization performance was evaluated under dynamic conditions with eight different combinations of acceleration and velocity. The ground truth accelerations varied from 0.6 to 1.6 m/s² and the ground truth velocities varied from 0.6 to 0.8 m/s. Our experimental results show that the location error can reach up to 50 cm under dynamic testing conditions when only relying on the UWB sensor, with the KF sensor fusion of UWB and IMU, the location error decreases to 13.7 cm.

Quantitative measurement of hand motion is essential in evaluating hand function. This study aimed to investigate the validity and reliability of a novel depth camera-based contactless automatic measurement system to assess hand range of motion and its potential benefits in clinical applications.

Five hand gestures were designed to evaluate the hand range of motion using a depth camera-based measurement system. Seventy-one volunteers were enrolled in performing the designed hand gestures. Then, the hand range of motion was measured with the depth camera and manual procedures. System validity was evaluated based on 3 dimensions: repeatability, within-laboratory precision, and reproducibility. For system reliability, linear evaluation, the intraclass correlation coefficient, paired t -test and bias were employed to test the consistency and difference between the depth camera and manual procedures.

When measuring phalangeal length, repeatability, within-laboratory precision, and reproducibility were 2.63%, 12.87%, and 27.15%, respectively. When measuring angles of hand motion, the mean repeatability and within-laboratory precision were 1.2° and 3.3° for extension of 5 digits, 2.7° and 10.2° for flexion of 4 fingers, and 3.1° and 5.3° for abduction of 4 metacarpophalangeal joints, respectively. For system reliability, the results showed excellent consistency (intraclass correlation coefficient = 0.823; P < .05) and good linearity with the manual procedures (r = 0.909-0.982, approximately; P < .001). Besides, 78.3% of the measurements were clinically acceptable.

Our depth camera-based evaluation system provides acceptable validity and reliability in measuring hand range of motion and offers potential benefits for clinical care and research in hand surgery. However, further studies are required before clinical application.

This study suggests a depth camera-based contactless automatic measurement system holds promise for assessing hand range of motion in hand function evaluation, diagnosis, and rehabilitation for medical staff. However, it is currently not adequate for all clinical applications.

To investigate the effect of traditional Chinese manual therapy (TCMT) in alleviating pain and dysfunction in patients with lumbar disc herniation (LDH).

Sixty-six patients with LDH were recruited as the study cohort and randomly assigned to an observation group and a control group. The patients in the observation group underwent TCMT, whereas those in the control group underwent conventional lumbar traction (LT). The observed indexes comprised primary index, which referred to clinical efficacy, and secondary indexes, which include Simplified McGill Pain Questionnaire, Oswestry Disability Index (ODI), range of motion (ROM) of the lumbar spine, difference in muscle tone (MT) and pressure pain threshold (PPT) of the bilateral erector spinae, and serum inflammatory factor levels.

The total effective rate was significantly higher in the observation group than in the control group (96.67% vs. 66.67%, P < 0.001). Compared with the control group after treatment, patients in the observation group had significantly lower ODI, pain rating index, visual analog scale and present pain intensity scores (all P < 0.05), and had significantly smaller differences in MT and PPT of the bilateral erector spinae (both P < 0.001), but had remarkably greater ROM of the lumbar spine (P < 0.001). In addition, interleukin (IL)-6, IL-8, and interferon-γ concentrations in the observation group were significantly lower than those in the control group after treatment (all P < 0.05).

TCMT has positive effects on alleviating pain and improving dysfunction of patients with LDH and helps in reducing serum inflammatory factor levels.