Yoma Matias, Herrington Lee, Starbuck Chelsea, Llurda Luis, Jones Richard
Department of Health Professions Manchester Metropolitan University.
School of Health and Society University of Salford.
Int J Sports Phys Ther. 2025 Aug 1;20(8):1160-1175. doi: 10.26603/001c.141870. eCollection 2025.
Markerless motion capture has the potential to repeatedly collect biomechanical data during activities associated with injuries. Few studies have assessed the reliability of this technology during single-leg tasks.
The primary aim was to examine the between-day reliability of trunk and lower limb kinematics during single-leg squat and single-leg landing tasks using markerless motion capture. The secondary aim was to examine the between-day reliability of the same protocol using marker-based motion capture.
Reliability.
Nineteen recreational athletes performed all tasks in two sessions, one week apart. Joint angles of trunk, hip, knee, and ankle were processed using Theia3D. A separate study (10 different participants) evaluated the reliability of marker-based motion capture. In both technologies, full curve analysis was examined using root mean square difference (RMSD) and discrete point analysis (initial contact and peak knee flexion) using intraclass correlation coefficient (ICC) and standard error of measurement (SEM). Statistical parametric mapping (SPM) was also used for full curve analysis in markerless motion capture.
For full curve analysis, markerless motion capture demonstrated low mean RMSD for all joints and planes in both SLS (3.6˚±1.3˚) and landing tasks (forward=3.2˚±1.3˚; medial=3.4˚±1.7˚). SPM showed statistical difference for bilateral hip flexion (full curve) and unilateral hip adduction, rotation, and knee flexion during a percentage of landing tasks. For discrete point analysis, ICC mean indicated moderate to good reliability (SLS= 0.77; forward landing= 0.83; medial landing= 0.80) with low mean SEM values (SLS=3.1°±1.3˚; forward landing=2.3˚±0.9°; medial landing=2.3˚±0.8˚). Marker-based motion capture showed slightly higher mean RMSD (SLS=4.2˚±1.8˚; forward landing=3.5˚±1.0˚; medial landing=3.3˚±0.9) and SEM values (SLS=4.1˚±2.2˚; forward landing=2.7˚±1.2°; medial landing=2.8˚±1.2˚). ICC mean showed good relative reliability (SLS=0.90; forward landing=0.88; medial landing=0.88). Hip flexion presented values >5° across tasks and technologies (RMSD and SEM= 5° to 8°).
Markerless motion capture using Theia3D can reliably measure single-leg tasks with measurement errors comparable to marker-based motion capture. The low measurement error provides confidence for the regular monitoring of athletes during single-leg tasks.
无标记运动捕捉技术有潜力在与损伤相关的活动中反复收集生物力学数据。很少有研究评估该技术在单腿任务中的可靠性。
主要目的是使用无标记运动捕捉技术检查单腿深蹲和单腿落地任务期间躯干和下肢运动学的日间可靠性。次要目的是使用基于标记的运动捕捉技术检查相同方案的日间可靠性。
可靠性研究。
19名休闲运动员在两个时间段内完成所有任务，间隔一周。使用Theia3D处理躯干、髋、膝和踝关节的关节角度。另一项研究（10名不同参与者）评估了基于标记的运动捕捉技术的可靠性。在这两种技术中，使用均方根差（RMSD）进行全曲线分析，并使用组内相关系数（ICC）和测量标准误差（SEM）进行离散点分析（初始接触和膝关节最大屈曲）。在无标记运动捕捉的全曲线分析中还使用了统计参数映射（SPM）。
对于全曲线分析，无标记运动捕捉技术在单腿深蹲（3.6˚±1.3˚）和落地任务（向前=3.2˚±1.3˚；向内=3.4˚±1.7˚）中，所有关节和平面的平均RMSD均较低。SPM显示，在一定比例的落地任务中，双侧髋关节屈曲（全曲线）以及单侧髋关节内收、旋转和膝关节屈曲存在统计学差异。对于离散点分析，ICC平均值表明可靠性为中等至良好（单腿深蹲= 0.77；向前落地= 0.83；向内落地= 0.80），平均SEM值较低（单腿深蹲=3.1°±1.3˚；向前落地=2.3˚±0.9°；向内落地=2.3˚±0.8˚）。基于标记的运动捕捉技术的平均RMSD（单腿深蹲=4.2˚±1.8˚；向前落地=3.5˚±1.0˚；向内落地=3.3˚±0.9）和SEM值（单腿深蹲=4.1˚±2.2˚；向前落地=2.7˚±1.2°；向内落地=2.8˚±1.2˚）略高。ICC平均值显示出良好的相对可靠性（单腿深蹲=0.90；向前落地=0.88；向内落地=0.88）。在所有任务和技术（RMSD和SEM = 5°至8°）中，髋关节屈曲的值均>5°。
使用Theia3D的无标记运动捕捉技术能够可靠地测量单腿任务，其测量误差与基于标记的运动捕捉技术相当。低测量误差为在单腿任务期间定期监测运动员提供了信心。
3级。
