Study of functional electrical stimulation onset based on gait events and sEMG

Journal Information

J. Hefei Univ. Tech. (Nat. Sci.), May.2024, Vol.47 No.5: 590-595

DOI: 10.3969/j.issn.1003-5060.2024.05.003

Authors

DENG Changren $ ^{1,2} $, CHEN Enwei $ ^{1} $, ZHANG Jiafeng $ ^{1,2} $, WANG Yong $ ^{1,2} $

(1. School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China; 2. Intelligent Interconnected Systems Laboratory of Anhui Province, Hefei University of Technology, Hefei 230009, China)

Abstract and Keywords

Abstract: Functional electrical stimulation during foot drop walking can help patients restore their normal walking ability. Therefore, it is very important to accurately determine the on-time of functional electrical stimulation. To address this problem, this paper used the angular velocity of the lower limbs and surface electromyography (sEMG) signals during walking to explore a method of controlling the delay relationship between gait events and muscle action points as a control strategy for the accurate determination of functional electrical stimulation onset during foot drop walking. According to the characteristics of gait information and sEMG signals, this paper designed a wireless acquisition device, and then divided the angular velocity data of the thighs into gait events. The experimental results show that the gait event division has good consistency. The fuzzy entropy algorithm was used to determine the muscle movement onset $ T_{muscle} $ from the denoised sEMG signals, to determine the delay relationship between $ T_{muscle} $ and toe off (TO), and to determine the electrical stimulation onset $ T_{on} $ by combining the delineated gait event characteristic points. This study provides a new identification method for the accurate onset of functional electrical stimulation in foot drop treatment.

Keywords: gait analysis; surface electromyography(sEMG); fuzzy entropy; functional electrical stimulation onset; foot drop

作者信息

邓昌仁 $ ^{1,2} $，陈恩伟 $ ^{1} $，张佳峰 $ ^{1,2} $，王勇 $ ^{1,2} $

(1. 合肥工业大学机械工程学院，安徽合肥 230009；2. 合肥工业大学智能互联系统安徽省实验室，安徽合肥 230009)

摘要和关键词

摘要: 足下垂患者步行过程中进行功能性电刺激可以帮助其恢复正常行走能力, 而准确确定功能性电刺激的开启时间至关重要。文章针对该问题, 利用步行过程中下肢的角速度和表面肌电信号(surface electromyography, sEMG), 提出一种以步态事件与肌肉动作点之间延时关系为控制策略的足下垂步行过程中功能性电刺激准确开启的方法。根据步态信息和 sEMG 电信号特征对大腿处的角速度数据进行步态事件划分, 试验结果表明步态事件划分得具有良好一致性; 利用模糊熵算法对去噪后的 sEMG 信号进行肌肉运动起始点 $ T_{muscle} $ 的判定, 确定 $ T_{muscle} $ 与脚尖离地 (toe off, TO) 之间的延时时间关系; 结合所划分的步态事件特征点, 确定电刺激起始点 $ T_{on} $ 。该文为足下垂治疗中功能性电刺激开启时间点的确定提供了一种新的辨识方法。

关键词: 步态分析；表面肌电信号（sEMG）；模糊熵；功能性电刺激起始点；足下垂

Funding

科技部中小企业创新基金资助项目（11C26213402042）；中央高校基本科研业务费专项资金资助项目（JZ2016YYP0066）和合肥市自然科学基金资助项目（2021031）

合肥工业大学学报(自然科学版)

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