Reliability of stride length estimation in self-pace and brisk walking with an inertial measurement unit on shank

R. Kasai, T. Kodama, Z. Gu, D. Zhang, W. Kong, S. Cosentino, S. Sessa, Y. Kawakami, A. Takanishi
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Abstract

The use of Inertial Measurement Unit (IMU) for gait analysis is gaining popularity because of its advantages of low cost and non-limited workspace. In this context, researchers are focusing on methods for automated data analysis. For example, many algorithms for stride length estimation have been developed. These algorithms rely on event detection to compute gait parameters during walking and on orientation estimation for a more precise double integration of acceleration. However, at the present, there is not comparison between existing algorithms, and the applicability of each algorithm for different walking patterns is not clear. In this paper, we studied the effect on the stride length estimation using three different techniques of event detection and two techniques of orientation estimation, by using an IMU on the lateral side of shank above the ankle. In total 6 patterns of stride estimation algorithms were compared on different walking patterns of normal and brisk walking. We evaluated the techniques in terms of precision, accuracy, and shape of the histogram of the stride estimation error.
用足部惯性测量装置估算自步快走步幅的可靠性
惯性测量单元(IMU)由于其成本低、工作空间不受限制等优点,在步态分析中得到了广泛的应用。在这种背景下,研究人员正在关注自动化数据分析的方法。例如,已经开发了许多步长估计算法。这些算法依赖于事件检测来计算行走过程中的步态参数,并依赖于方向估计来获得更精确的加速度双积分。但是,目前并没有对现有算法进行比较,而且每种算法对于不同行走模式的适用性也不明确。在本文中,我们研究了三种不同的事件检测技术和两种方向估计技术对步长估计的影响,在脚踝以上的小腿外侧使用IMU。比较了6种步幅估计算法在正常步行和快走两种不同步行方式下的差异。我们从精度、准确度和步幅估计误差直方图的形状方面对这些技术进行了评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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