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.

中文翻译：

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现实生活中步行条件下基于IMU的无磁强计的脚行进角估计

足部前进角（FPA）在许多疾病评估和康复应用中至关重要，但是，以前基于磁-IMU的FPA估计算法在步行开始和转弯后可能容易出现磁变形和不准确的情况。本文提出了一种基于IMU的磨损FPA估计算法，该算法包括三个关键部分：方向估计，加速度变换和通过峰脚减速度进行FPA估计。12名健康受试者进行了两次步行实验，以评估IMU算法的性能。第一个实验旨在在7种FPA步态模式（大脚趾，中脚趾，小脚趾，正常，小脚趾，中脚趾和大脚趾）的连续直行任务中验证所提出的算法-出去）。进行第二个实验，以评估提出的FPA算法在步行开始和转弯后的步伐。结果表明，基于IMU的算法进行的FPA估算紧随基于标记的系统测量，总体平均绝对误差为3.1±1.3度，并且该估算结果在步行开始和转弯后的所有步骤中均有效。这项工作可以在因黑色金属结构和电气设备而导致磁畸变的环境中，或者在实际的步行条件下（通常发生步行开始，停止和转弯）进行FPA评估。步行开始和转弯后，估计结果对所有步骤均有效。这项工作可以在因黑色金属结构和电气设备而导致磁畸变的环境中，或者在实际的步行条件下（通常发生步行开始，停止和转弯）进行FPA评估。步行开始和转弯后，估计结果对所有步骤均有效。这项工作可以在因黑色金属结构和电气设备而导致磁畸变的环境中，或者在实际的步行条件下（通常发生步行开始，停止和转弯）进行FPA评估。