中国组织工程研究

中国组织工程研究 ›› 2011, Vol. 15 ›› Issue (22): 4103-4106.doi: 10.3969/j.issn.1673-8225.2011.22.027

• 数字化骨科 digital orthopedics • 上一篇    下一篇

采集表面肌电信号应用于动作识别的可行性

卢  蕾，殷  涛，靳静娜，李  颖，刘志朋   

  1. 中国医学科学院北京协和医学院生物医学工程研究所，天津市  300192
  • 收稿日期:2011-01-06 修回日期:2011-04-08 出版日期:2011-05-28 发布日期:2011-05-28
  • 通讯作者: 刘志朋，硕士，中国医学科学院北京协和医学院生物医学工程研究所，天津市 300192 bme500@163.com
  • 作者简介:卢蕾★，女，1985年生，山东省泰安市人，汉族，北京协和医学院生物医学工程研究所在读硕士，主要从事低成本、高可靠性、多功能中医针灸治疗研制与产业化研究。 Lzpeng67@163.com
  • 基金资助:

    科技部十一五科技支撑计划项目(2007BAI07A18)资助。

Feasibility of surface electromyography signal acquisition for action recognition

Lu Lei, Yin Tao, Jin Jing-na, Li Ying, Liu Zhi-peng   

  1. Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin  300192, China
  • Received:2011-01-06 Revised:2011-04-08 Online:2011-05-28 Published:2011-05-28
  • Contact: Liu Zhi-peng, Master, Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300192, China bme500@163.com
  • About author:Lu Lei★, Studying for master’s degree, Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300192, China Lzpeng67@163.com
  • Supported by:

    the Science and Technology Support Project during the Eleventh Five-year Period, Ministry of Science and Technology, No. 2007BAI07A18*

PDF

794

被引次数

22

摘要：

背景：文献表明上肢前臂运动时所产生的表面肌电信号具有非线性特征，而肢体运动时肌电信号又呈现出非平稳特性。
目的：设计一种简单的拾取电路采集表面肌电信号，拟应用于动作肌电信号的特征识别。
方法：根据表面肌电信号的特点，设计高共模抑制比的前端放大电路，抑制共模干扰；采用低通滤波电路，有源双T带阻滤波器对信号进行去噪处理；对采集得到的信号进行小波包变换，得到信号的特征量。
结果与结论：所设计的表面肌电信号检测电路具有较高共模抑制比，并能有效地滤除50 Hz工频信号，可以满足肌电信号采集电路的基本要求。肌电信号的处理结果表明采用子频段能量值的方法可以区分手部4种不同动作。

关键词: 表面肌电信号, 信号检测, 去噪处理, 小波包变换, 数字化医学

Abstract:

BACKGROUND: Surface electromyography (sEMG) are widely adopted because of its scot-free. Because of the non-stationary of signals, sEMG signals can be classified in wavelet packet transform to obtain effective parameters.
OBJECTIVE: To design a detection circuit according to the characteristics of the sEMG, which can pick-up the SEMG signals for action recognition.
METHODS: The high CMMR preamplifier was designed to restrain the common code interference; low-pass filter and active double-T band-stop filter were carried on de-noising processing; sEMG signals could be classified in wavelet packet transform to obtain effective parameters.
RESULTS AND CONCLUSION: In the experiment, the circuit could implement the anticipated target, pick-up the sEMG and restrain the interference with 50 Hz; further, four different actions on hands could be recognized by using sub band energy value extracted in the wavelet packet translation of the sEMG.

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