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惯性传感用于步态事件检测和仿生膝关节控制策略。

Inertial Sensing for Gait Event Detection and Transfemoral Prosthesis Control Strategy.

出版信息

IEEE Trans Biomed Eng. 2018 Dec;65(12):2704-2712. doi: 10.1109/TBME.2018.2813999. Epub 2018 Mar 9.

Abstract

OBJECTIVE

This paper presents a method for walking gait event detection using a single inertial measurement unit (IMU) mounted on the shank.

METHODS

Experiments were conducted to detect heel strike (HS) and toe off (TO) gait events of 10 healthy subjects and 5 transfemoral amputees walking at various speeds and slopes on an instrumented treadmill. The performance of three different algorithms [thresholding (THR), linear discriminant analysis, and quadratic discriminant analysis] was evaluated on both timing and frequency of gait event detections compared to data collected using force plates.

RESULTS

Though all algorithms could be used reliably (within 8.2% stride temporal error and 0.2% frequency error), THR was the most accurate, detecting 100% of gait events within an average of 2% stride for both the healthy subjects and the amputees. Furthermore, universal parameters could be used across all speeds and slopes within each demographic.

CONCLUSION

HS and TO for walking gait can be reliably detected in healthy and transfemoral amputee subjects using a single IMU.

SIGNIFICANCE

This work provides a robust, simple, and inexpensive method of gait event detection that does not rely on a load cell and could be easily implemented in a lower-limb prosthesis.

摘要

目的

本文提出了一种使用安装在小腿上的单个惯性测量单元(IMU)检测行走步态事件的方法。

方法

对 10 名健康受试者和 5 名股骨截肢者在带有仪器的跑步机上以不同速度和坡度行走时的足跟触地(HS)和脚趾离地(TO)步态事件进行了实验。与使用测力板收集的数据相比,评估了三种不同算法(阈值法(THR)、线性判别分析和二次判别分析)在步态事件检测的时间和频率上的性能。

结果

虽然所有算法都可以可靠地使用(步长时间误差在 8.2%以内,频率误差在 0.2%以内),但 THR 是最准确的,对于健康受试者和截肢者,平均 2%的步长内可以检测到 100%的步态事件。此外,在每个人群中,对于所有速度和坡度,都可以使用通用参数。

结论

使用单个 IMU 可以可靠地检测健康和股骨截肢受试者的行走步态中的 HS 和 TO。

意义

这项工作提供了一种可靠、简单且经济的步态事件检测方法,它不依赖于测力板,并且可以很容易地在下肢假肢中实现。

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