运动学
步态
工件(错误)
大腿
运动捕捉
计算机科学
软组织
单调的工作
流离失所(心理学)
星团(航天器)
生物医学工程
解剖
人工智能
医学
物理
运动(物理)
物理医学与康复
病理
物理疗法
程序设计语言
心理治疗师
经典力学
心理学
作者
Annick Barre,Brigitte M. Jolles,Nicolas Theumann,Kamiar Aminian
标识
DOI:10.1016/j.jbiomech.2015.04.007
摘要
Segment poses and joint kinematics estimated from skin markers are highly affected by soft tissue artifact (STA) and its rigid motion component (STARM). While four marker-clusters could decrease the STA non-rigid motion during gait activity, other data, such as marker location or STARM patterns, would be crucial to compensate for STA in clinical gait analysis. The present study proposed 1) to devise a comprehensive average map illustrating the spatial distribution of STA for the lower limb during treadmill gait and 2) to analyze STARM from four marker-clusters assigned to areas extracted from spatial distribution. All experiments were realized using a stereophotogrammetric system to track the skin markers and a bi-plane fluoroscopic system to track the knee prosthesis. Computation of the spatial distribution of STA was realized on 19 subjects using 80 markers apposed on the lower limb. Three different areas were extracted from the distribution map of the thigh. The marker displacement reached a maximum of 24.9 mm and 15.3 mm in the proximal areas of thigh and shank, respectively. STARM was larger on thigh than the shank with RMS error in cluster orientations between 1.2° and 8.1°. The translation RMS errors were also large (3.0 mm to 16.2 mm). No marker-cluster correctly compensated for STARM. However, the coefficient of multiple correlations exhibited excellent scores between skin and bone kinematics, as well as for STARM between subjects. These correlations highlight dependencies between STARM and the kinematic components. This study provides new insights for modeling STARM for gait activity.
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