Mechanical and Materials Engineering, Queen's University, Kingston ON Canada.
Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada; Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada.
J Biomech. 2023 May;152:111556. doi: 10.1016/j.jbiomech.2023.111556. Epub 2023 Mar 27.
Balance tests have clinical utility in identifying balance deficits and supporting recommendations for appropriate treatments. Motion capture technology can be used to measure whole-body kinematics during balance tasks, but to date the high technical and financial costs have limited uptake of traditional marker-based motion capture systems for clinical applications. Markerless motion capture technology using standard video cameras has the potential to provide whole-body kinematic assessments with clinically accessible technology. Our aim was to quantify poses and movement strategies during static balance tasks (tandem stance, single limb stance, standing hip abduction, and quiet standing on foam with eyes closed) using video-based markerless motion capture software (Theia3D) and principal component analysis to examine the associations with age, body mass index (BMI) and sex. In 30 healthy adults, the mean poses for all balance tasks had at least one principal component (PC) that differed significantly by sex. Age was significantly associated with the PC describing leg height for the hip abduction task and erect posture for the quiet standing task. BMI was significantly associated with the PC capturing knee flexion in the single leg stance task. The movement strategies used to maintain balance showed significant differences by sex for the tandem stance pose. BMI was correlated with PCs for movement strategies for hip abduction and quiet standing tasks. Results from this study demonstrate how markerless motion capture technology could be used to augment analyses of balance both in the clinic and in the field.
平衡测试在识别平衡缺陷和支持适当治疗建议方面具有临床应用价值。运动捕捉技术可用于测量平衡任务中的全身运动学,但迄今为止,传统基于标记的运动捕捉系统的高技术和财务成本限制了其在临床应用中的采用。使用标准摄像机的无标记运动捕捉技术有可能利用临床可及的技术提供全身运动学评估。我们的目的是使用基于视频的无标记运动捕捉软件(Theia3D)和主成分分析来量化静态平衡任务(并足站立、单腿站立、站立髋关节外展和闭眼站在泡沫上)中的姿势和运动策略,以检查其与年龄、体重指数(BMI)和性别的相关性。在 30 名健康成年人中,所有平衡任务的平均姿势都至少有一个主成分(PC)因性别而异。年龄与描述髋关节外展任务中腿部高度和安静站立任务中直立姿势的 PC 显著相关。BMI 与单腿站立任务中捕捉膝关节弯曲的 PC 显著相关。用于维持平衡的运动策略在并足站立姿势方面因性别而异。BMI 与髋关节外展和安静站立任务的运动策略的 PC 相关。本研究的结果表明,无标记运动捕捉技术如何可用于增强临床和现场的平衡分析。