IEEE Trans Neural Syst Rehabil Eng. 2021;29:282-289. doi: 10.1109/TNSRE.2020.3047402. Epub 2021 Mar 2.
Foot progression angle (FPA) is vital in many disease assessment and rehabilitation applications, however previous magneto-IMU-based FPA estimation algorithms can be prone to magnetic distortion and inaccuracies after walking starts and turns. This paper presents a foot-worn IMU-based FPA estimation algorithm comprised of three key components: orientation estimation, acceleration transformation, and FPA estimation via peak foot deceleration. Twelve healthy subjects performed two walking experiments to evaluation IMU algorithm performance. The first experiment aimed to validate the proposed algorithm in continuous straight walking tasks across seven FPA gait patterns (large toe-in, medium toe-in, small toe-in, normal, small toe-out, medium toe-out, and large toe-out). The second experiment was performed to evaluate the proposed FPA algorithm for steps after walking starts and turns. Results showed that FPA estimations from the IMU-based algorithm closely followed marker-based system measurements with an overall mean absolute error of 3.1±1.3 deg, and the estimation results were valid for all steps immediately after walking starts and turns. This work could enable FPA assessment in environments where magnetic distortion is present due to ferrous metal structures and electrical equipment, or in real-life walking conditions when walking starts, stops, and turns commonly occur.
足进角(FPA)在许多疾病评估和康复应用中至关重要,然而以前基于磁-惯性测量单元(magneto-IMU)的 FPA 估计算法在开始行走和转弯后可能容易受到磁场扭曲和不准确性的影响。本文提出了一种基于穿戴式 IMU 的 FPA 估计算法,由三个关键组件组成:方向估计、加速度转换以及通过峰值足部减速的 FPA 估计。12 名健康受试者进行了两项行走实验,以评估 IMU 算法的性能。第一项实验旨在验证该算法在七种 FPA 步态模式(大趾内翻、中趾内翻、小趾内翻、正常、小趾外翻、中趾外翻和大趾外翻)的连续直线行走任务中的性能。第二项实验是为了评估该算法在行走开始和转弯后的步伐中的 FPA 算法。结果表明,基于 IMU 的算法的 FPA 估计与基于标记的系统测量密切相关,总体平均绝对误差为 3.1±1.3 度,并且估计结果适用于行走开始和转弯后立即的所有步伐。这项工作可以实现在由于铁磁金属结构和电气设备导致磁场扭曲的环境中进行 FPA 评估,或者在行走开始、停止和转弯经常发生的现实生活行走条件下进行 FPA 评估。