Evaluation of the Ergomechanic markerless motion capture system for lower body kinematics during standing, squatting and walking.

IF 1.7 4区 医学 Q4 BIOPHYSICS
Simon Harrison, Raymond C Z Cohen, Scott Starkey, Jayan Greenwood, Ernest Cheong, Khoi Nguyen, Phu Trinh, Tomislav Bacek, Denny Oetomo
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Abstract

Markerless motion capture (MMC) shows promise for examining human movement across many domains because of its non-intrusive nature and negligible per-subject set up time. However published MMC systems typically require specific hardware. This validation study compared lower-body joint kinematics from Ergomechanic, a hardware-agnostic pose model-based MMC system, to an established marker-based motion capture (MBMC) system. Static trial data from eighteen people were used to register MMC keypoints within a widely used musculoskeletal model. The registered model was used to calculate joint kinematics for static pose, squatting, and walking trials. A novel perturbation analysis estimated the contributions to differences in MBMC and MMC approaches to measurement disparities. Very good (0.87 to 1.0) correlations between the systems were calculated for ankle, knee, and hip flexion-extension angles. Good (0.70-0.86) correlations were found for hip external-internal and abduction-adduction. Pelvis and lumbar spine angles had a wider range of correlation results (-0.06 to 0.95), likely due to the few MMC keypoints in these body regions. Relative contributions from the perturbation analysis were (i) 75% from variations in MMC data relative to MBMC; (ii) 8% because MMC keypoints (26) < MBMC markers (67); and (iii) 3% from differences in musculoskeletal model scaling. These results validate Ergomechanic for leg kinematics during standing, walking and squatting. Further, they suggest system improvements for pelvis and torso kinematics and provide new insights into the sources of known differences between MMC and MBMC measurements.

对站立、下蹲和行走时下体运动学的人机力学无标记运动捕捉系统的评估。
无标记动作捕捉(MMC)由于其非侵入性和可忽略的每个受试者设置时间,显示出在许多领域检查人类运动的希望。然而,发布的MMC系统通常需要特定的硬件。该验证研究比较了ergomechanics(基于硬件不可知姿态模型的MMC系统)和已建立的基于标记的运动捕捉(MBMC)系统的下半身关节运动学。来自18人的静态试验数据用于在广泛使用的肌肉骨骼模型中记录MMC关键点。注册模型用于计算静态姿势、下蹲和步行试验的关节运动学。一种新的微扰分析估计了MBMC和MMC测量方法差异的贡献。计算出踝关节、膝关节和髋关节屈伸角之间非常好的相关性(0.87至1.0)。髋外-内和外展-内收的相关性良好(0.70-0.86)。骨盆和腰椎角度的相关结果范围更广(-0.06至0.95),可能是由于这些身体区域的MMC关键点较少。摄动分析的相对贡献为(i) 75%来自MMC数据相对于MBMC的变化;(ii) 8%是因为MMC关键点(26)< MBMC标记(67);(iii) 3%来自肌肉骨骼模型缩放的差异。这些结果验证了站立、行走和下蹲时腿部运动学的人机工程学。此外,他们建议骨盆和躯干运动学的系统改进,并为MMC和MBMC测量之间已知差异的来源提供了新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.40
自引率
5.90%
发文量
169
审稿时长
4-8 weeks
期刊介绍: Artificial Organs and Prostheses; Bioinstrumentation and Measurements; Bioheat Transfer; Biomaterials; Biomechanics; Bioprocess Engineering; Cellular Mechanics; Design and Control of Biological Systems; Physiological Systems.
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