ikneebrace:步态检测中运动传感器测量的膝关节内收力矩评估

Hsin-Ruey Tsai, Shih-Yao Wei, Jui-Chun Hsiao, Ting-Wei Chiu, Yi-Ping Lo, Chi-Feng Keng, Y. Hung, Jin-Jong Chen
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引用次数: 10

摘要

我们提出轻量级可穿戴设备iKneeBraces,通过膝关节内收力矩(KAM)评估来预防膝关节骨关节炎(OA)。iKneeBrace由两个惯性测量单元(imu)组成,用于测量胫骨和大腿的角度。KAM是通过地面反力(GRF)、膝盖位置和压力中心位置来估算的。代替传统使用的笨重的三维力板,我们建议建立一个2D输入回归模型,使用iKneeBrace的胫骨和大腿角度作为输入来推断GRF方向并进一步估计KAM。我们做了一个实验来评估这种方法。结果表明,iKneeBrace可以在第一个峰值推断出与地面真实相似的KAM,这是预防膝关节OA最重要的部分。此外,如果未来iKneeBrace使用更好的imu,所提出的方法可以推断出所有部件的KAM。所提出的方法不仅使KAM评估便携,而且只需要轻量级的设备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
iKneeBraces: knee adduction moment evaluation measured by motion sensors in gait detection
We propose light-weight wearable devices, iKneeBraces, to prevent knee osteoarthritis (OA) using knee adduction moment (KAM) evaluation. iKneeBrace consists of two inertial measurement units (IMUs) to measure shin and thigh angles. KAM is estimated by ground force reaction (GRF), knee position and center of pressure position. Instead of heavy and bulky 3DoF force plates conventionally used, we propose to build a 2D input regression model using shin and thigh angles from iKneeBrace as input to infer GRF direction and further estimate KAM. We perform an experiment to evaluate the method. The results show that iKneeBrace can infer KAM similar to the ground truth in the first peak, the most important part to prevent knee OA. Furthermore, the proposed method can infer KAM in all parts if better IMUs used in iKneeBrace in the future. The proposed method not only makes KAM evaluation portable but also requires only light-weight devices.
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