Real-time gait event detection using wearable sensors
Real-time gait event detection using wearable sensors
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DOI：
10.1016/j.gaitpost.2009.07.128
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发表时间：
2009-11-01
期刊：
影响因子：
2.4
通讯作者：
Anderson, Ross
中科院分区：
文献类型：
--
作者：
Hanlon, Michael;Anderson, Ross
实时步态事件检测是功能性电刺激和步态生物反馈的要求。理想情况下，这种步态事件检测应该使用耐用、轻便、低成本传感器的便携式系统来实现。先前的研究报告了脚踏开关系统的耐久性问题。因此，本研究描述了在12名健康个体中使用脚踏开关和加速计传感器的新型检测算法的开发和评估。受试者在脚跟上配备一个力敏电阻器，在脚上配备一个加速度计，在膝盖上配备一个加速度计。受试者在三种条件下进行10，8米步行试验：正常，缓慢和改变（减少膝关节ROM）步行。来自四个受试者的子集的数据用于开发初始接触（IC）的预测算法。随后，针对标准测力板IC数据（上升沿阈值为5 N），在其余8名受试者上测试这些算法。脚踏开关力阈值算法对于IC检测最准确（平均绝对误差为2.4 +/- 2.1 ms），并且比最佳加速度计算法（平均绝对误差为9.5 +/- 9.0 ms）显著更准确（p < 0.001）。最佳加速度计算法使用来自两个加速度计的数据，其中IC由脚前后加速度的二阶导数确定。脚踏开关和加速度计算法的误差结果低于（类似于60%）先前关于动态实时步态事件检测系统的研究。目前，脚踏开关系统必须优于加速度计系统，以准确检测IC，然而，由于其耐用，低成本传感器的优势，值得进一步研究加速度计算法。(C)2009 Elsevier B. V.保留所有权利。
Real-time gait event detection is a requirement for functional electrical stimulation and gait biofeedback. This gait event detection should ideally be achieved using an ambulatory system of durable, lightweight, low-cost sensors. Previous research has reported issues with durability in footswitch systems. Therefore, this study describes the development and assessment of novel detection algorithms using footswitch and accelerometer sensors on 12 healthy individuals. Subjects were equipped with one force sensitive resistor on the heel, one accelerometer at the foot, and one accelerometer at the knee. Subjects performed 10, 8-m walking trials in each of three conditions: normal, slow, and altered (reduced knee ROM) walking. Data from a subset of four subjects were used to develop prediction algorithms for initial contact (IC). Subsequently, these algorithms were tested on the remaining eight subjects against standard forceplate IC data (threshold of 5 N on a rising edge). The footswitch force threshold algorithm was most accurate for IC detection (mean absolute error of 2.4 +/- 2.1 ms) and was significantly more accurate (p < 0.001) than the optimal accelerometer algorithm (mean absolute error of 9.5 +/- 9.0 ms). The optimal accelerometer algorithm used data from both accelerometers, with IC determined from the second derivative of foot fore-aft acceleration. The error results for footswitch and accelerometer algorithms are lower (similar to 60%) than in previous research on ambulatory real-time gait event detection systems. Currently, footswitch systems must be recommended over accelerometer systems for accurate detection of IC, however, further research into accelerometer algorithms is merited due to its advantages as a durable, low-cost sensor. (C) 2009 Elsevier B.V. All rights reserved.