角速度信号在功能性电刺激系统步态分段算法中的应用

Angular velocity signal applied to gait segmentation algorithm in functional electrical stimulation system

研究可应用于功能性电刺激输出控制的步态识别算法,利用MEMS传感器采集步态的角速度数据,通过设置阈值实时识别患者行走时的摆动相,在脚跟离地时刻开启功能性电刺激,在脚跟着地时刻停止电刺激.平地自由行走模式和跑步机平台下的实验结果表明:该算法对脚跟离地和脚跟着地两个时刻的识别率分别大于97%和98%.本算法不需要积分运算,避免了累积误差,步态分段准确性高且算法简单,易于在单片机中实现,为研究穿戴式功能性电刺激系统提供了基础与保证.

A gait segmentation algorithm applied in functional electrical stimulation output control was studied in this paper.The angular velocity data was gotten by MEMS sensor,which can identify patients with the swing phase when walking in real time by set the threshold.The functional electrical stimulation was opened in heel off and stopped in heel strike.The results of walking mode and treadmill mode showed that the recognition rate of heel off and heel strike was over 97%and 98%respectively.This algorithm does not require integration calculation,so it can avoid the cumulative error and predict the gait fragmentation accurately.It is simple enough to be implemented in the microcontroller,guaranteeing the study of wearable functional electrical stimulation system.