Acceleration and electromyography (EMG) pattern analysis for children with cerebral palsy

Qian Wang, Xiang Chen, De Wu, Lingling Qian, Xu Zhang
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引用次数: 9

Abstract

This paper presents a framework of gait analysis for children with cerebral palsy (CP) using electromyography (EMG) and acceleration (ACC) signals. In this framework, ACC signals are firstly processed for stride cycle detection and segmentation, and then utilized to reveal kinematic information associated with gait abnormality, whereas the EMG signals are adopted to assess abnormal muscle activation patterns during gait movement. Six CP children with gait abnormalities were recruited to form the CP group , and two children with TD (typical development) were also recruited as the control group for gait analysis experiments. EMG signals from four typical muscles of both legs and vertical acceleration of shanks were collected simultaneously. It can be demonstrated from the experimental results that the proposed method is able to extract ACC and EMG patterns, indicating its clinical potential for the assessment and therapy of lower extremity functions for children with CP.
脑性麻痹儿童的加速和肌电图(EMG)模式分析
本文提出了一种基于肌电图(EMG)和加速(ACC)信号的脑瘫儿童步态分析框架。在该框架中,首先对ACC信号进行步幅周期检测和分割,然后利用ACC信号揭示与步态异常相关的运动学信息,然后利用肌电图信号评估步态运动过程中异常的肌肉激活模式。选取步态异常的CP患儿6例作为CP组,同时选取典型发育的TD患儿2例作为对照组,进行步态分析实验。同时采集双腿四个典型肌肉和小腿垂直加速度的肌电图信号。实验结果表明,该方法能够提取ACC和EMG模式,在CP患儿下肢功能评估和治疗方面具有临床应用潜力。
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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