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利用无线惯性传感器进行步态分析的足跟和脚趾间隙估计。

Heel and toe clearance estimation for gait analysis using wireless inertial sensors.

机构信息

Laboratory of Movement Analysis and Measurements, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.

出版信息

IEEE Trans Biomed Eng. 2012 Nov;59(11):3162-8. doi: 10.1109/TBME.2012.2216263. Epub 2012 Sep 4.

Abstract

Tripping is considered a major cause of fall in older people. Therefore, foot clearance (i.e., height of the foot above ground during swing phase) could be a key factor to better understand the complex relationship between gait and falls. This paper presents a new method to estimate clearance using a foot-worn and wireless inertial sensor system. The method relies on the computation of foot orientation and trajectory from sensors signal data fusion, combined with the temporal detection of toe-off and heel-strike events. Based on a kinematic model that automatically estimates sensor position relative to the foot, heel and toe trajectories are estimated. 2-D and 3-D models are presented with different solving approaches, and validated against an optical motion capture system on 12 healthy adults performing short walking trials at self-selected, slow, and fast speed. Parameters corresponding to local minimum and maximum of heel and toe clearance were extracted and showed accuracy ± precision of 4.1 ± 2.3 cm for maximal heel clearance and 1.3 ± 0.9 cm for minimal toe clearance compared to the reference. The system is lightweight, wireless, easy to wear and to use, and provide a new and useful tool for routine clinical assessment of gait outside a dedicated laboratory.

摘要

绊倒被认为是老年人跌倒的主要原因。因此,足离地间隙(即摆动阶段脚离地面的高度)可能是更好地理解步态与跌倒之间复杂关系的关键因素。本文提出了一种使用足部穿戴式无线惯性传感器系统来估计间隙的新方法。该方法依赖于传感器信号数据融合计算脚的姿态和轨迹,结合脚趾离地和脚跟触地事件的时间检测。基于自动估计传感器相对于脚的位置的运动学模型,估计脚跟和脚趾轨迹。提出了二维和三维模型,具有不同的求解方法,并针对 12 名健康成年人在自选择的慢走和快走速度下进行的短步行试验,使用光学运动捕捉系统进行了验证。提取了脚跟和脚趾离地间隙局部最小值和最大值对应的参数,与参考值相比,最大脚跟离地间隙的准确度±精度为 4.1±2.3cm,最小脚趾离地间隙的准确度±精度为 1.3±0.9cm。该系统重量轻、无线、易于穿戴和使用,为在专用实验室外常规临床评估步态提供了一种新的有用工具。

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