中国组织工程研究 ›› 2012, Vol. 16 ›› Issue (26): 4834-4840.doi: 10.3969/j.issn.1673-8225.2012.26.017

• 骨与关节损伤基础实验 basic experiments of bone and joint injury • 上一篇    下一篇

基于表面肌电的步态分析

王 静1,吴效明2   

  1. 1Department of Biomedical Engineering, Xinhua College of Sun Yat-Sen University, Guangzhou 510520, Guangdong Province, China;
    2Department of Biomedical Engineering, South China University of Technology, Guangzhou 510006, Guangdong Province, China
  • 收稿日期:2011-12-05 修回日期:2012-01-05 出版日期:2012-06-24 发布日期:2013-11-02
  • 通讯作者: 吴效明,博士,教授,华南理工大学生物医学工程系,广东省广州市 510006 bmxmwus@scut.edu.cn
  • 作者简介:王静★,女,1985年生,湖北省随州市人,汉族,2010年华南理工大学与广州体育学院(联合培养)毕业,硕士,助教,主要从事生物信号处理及步态功能评价研究。 happyjing00@163.com
  • 基金资助:

    华南理工大学天河区科技计划项目(096G135)

Gait analysis based on surface electromyography

Wang Jing1, Wu Xiao-ming2   

  1. 1中山大学新华学院生物医学工程系,广东省广州市 510520;
    2华南理工大学生物医学工程系,广东省广州市 510006
  • Received:2011-12-05 Revised:2012-01-05 Online:2012-06-24 Published:2013-11-02
  • Contact: Wu Xiao-ming, Doctor, Professor, Department of Biomedical Engineering, South China University of Technology, Guangzhou 510006, Guangdong Province, China bmxmwus@scut.edu.cn
  • About author:Wang Jing★, Master, Teaching assistant, Department of Biomedical Engineering, Xinhua College of Sun Yat-Sen University, Guangzhou 510520, Guangdong Province, China happyjing00@163.com

摘要:

背景:步态分析在人体运动系统和神经系统疾病的病因分析,诊断,功能、疗效与残疾评定中是重要的评价手段,其中肌肉活动是影响步行动力的基础因素。
目的:分析人体自然行走过程中下肢前后肌群的表面肌电变化,分析对应于步态周期不同时相前后肌群的表面肌电特征和机制。
方法:采用德国zebris FDM 步态分析系统(6 m)配套的同步肌电仪采集7例健康人正常步态过程中下肢胫骨前肌和腓肠肌外侧表面肌电信号,利用Matlab软件进行消噪和归一化,得到完整步态周期不同时相对应的表面肌电信号图,观察其峰值变化。采用芬兰ME6000肌电仪测试15 m自由行走人体左右侧下肢胫骨前肌和腓肠肌外侧表面肌电信号,提取时域和频域特征参数。
结果与结论:下肢胫骨前肌和腓肠肌外侧表面肌电信号在一个完整步态周期中呈特征性变化,即胫骨前肌表面肌电的峰值发生在后跟着地处,而腓肠肌外侧其峰值发生在中后支撑相处。进一步分析发现,人体在自由行走时其下肢肌肉优势侧与非优势侧差异有显著性意义(P < 0.05),且不同肌肉其差异趋势不同。

关键词: 表面肌电, 步态分析, 下肢肌群, 时域参数, 频域参数

Abstract:

BACKGROUND: Gait analysis is an important evaluation tool in etiological analysis and diagnosis of the human motor system and the nervous system, as well as the function, efficacy and disability evaluation, and muscle activity is the basic factor influencing walking power.
OBJECTIVE: To analyze the surface electromyography signal changes of lower limb muscles in the process of free walking, and to study the surface electromyography characteristics and mechanism corresponding to different gait phases.
METHODS: Seven cases of healthy people tibial anterior and lateral gastrocnemius surface electromyography signal were collected during normal gait by German Zebris FDM gait analysis system (6 m) simultaneous electromyography instrument, the signal was denoised and normalized by Matlab software, then the surface electromyography signal diagram that corresponded to various gait phases was obtained and the peak changes were observed; the 15 m free human walking bilateral tibial anterior and lateral gastrocnemius surface electromyography signals were tested by Finland ME6000 system, and then the time domain and frequency domain characteristic parameters were extracted.
RESULTS AND CONCLUSION: Tibial anterior and lateral gastrocnemius surface electromyography signals showed characteristic changes in a gait cycle, namely the tibial anterior surface electromyography peak occurred in the heel strike, but the lateral gastrocnemius surface electromyography peak occurred in the middle-rear support phase. There was significant difference of bilateral tibial anterior and lateral gastrocnemius characteristic parameters between the dominant side and non-dominant one (P < 0.05), and the change trend was different for different muscles.

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