[1]包其扬,王军霞,岳小力.基于子带频谱墒算法检测表面肌电信号肌肉疲劳性[J].中国医学物理学杂志,2020,37(10):1302-1305.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.015]
　BAO Qiyang,WANG Junxia,YUE Xiaoli.Detection of muscle fatigue based on surface electromyography signals segmented by subband spectral entropy algorithm[J].Chinese Journal of Medical Physics,2020,37(10):1302-1305.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.015]
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基于子带频谱墒算法检测表面肌电信号肌肉疲劳性()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
37
期数:
2020年第10期
页码:
1302-1305
栏目:
医学信号处理与医学仪器
出版日期:
2020-10-29

文章信息/Info

Title:
Detection of muscle fatigue based on surface electromyography signals segmented by subband spectral entropy algorithm
文章编号:
1005-202X（2020）10-1302-04
作者:
包其扬; 王军霞; 岳小力
中国人民解放军联勤保障部队第九四〇医院， 甘肃 兰州 730050
Author(s):
BAO Qiyang;  WANG Junxia;  YUE Xiaoli
No. 940 Hospital of the Joint Logistics Support Force of PLA, Lanzhou 730050, China
关键词:
子带频谱墒谱熵值; 表面肌电信号; 肌肉疲劳; 双阈值; 收缩区; 平均功率频率; 灵敏度波动比
Keywords:
Keywords: subband spectral entropy surface electromyography signal muscle fatigue double-threshold contraction region mean power frequency sensitivity to variability ratio
分类号:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2020.10.015
文献标志码:
A
摘要:
目的：针对传统检测肌肉疲劳方法灵敏度较差问题，提出按肌肉收缩区分割表面肌电信号。该方法考虑到肌肉动态收缩时肌肉发力、形状等因素影响特征参数平均功率频率的表征效果，因此，在分割表面肌电信号上以肌肉收缩区的个数作为单位，摒弃以时间作为单位的传统分割。方法：采用单参数结合双阈值的方法判断肌肉收缩区起、止点。利用肌肉动态收缩区特征参数平均功率频率的灵敏度波动比表征肌肉疲劳的灵敏度。表面肌电信号采集设备品牌为NORAXON、型号为MR3.6版本，程序设计采用MATLAB编程。结果与结论：仿真结果证明与传统定长分割方法相比，该方法检测肌肉疲劳具有较高的灵敏度和较好的表征性。
Abstract:
Abstract: Objective In view of the poor sensitivity of traditional methods for muscle fatigue detection, a new method is proposed to segment surface electromyography (sEMG) signals according to muscle contraction regions. Considering that the power and shape of muscle will affect the representation of the mean power frequency of the characteristic parameters when the muscle is in dynamic contraction, the number of muscle contraction regions instead of time is taken as the unit in sEMG signal segmentation. Methods The combining single-parameter and double-threshold is used to determine the starting and ending points of muscle contraction regions. The sensitivity of muscle fatigue is characterized by the sensitivity to variability ratio of the mean power frequency of the characteristic parameters of the dynamic contraction regions of muscle. The brand of sEMG acquisition equipment is NORAXON, and the model is MR3.6. MATLAB is used for programming. Results and Conclusion The simulation results show that compared with traditional fixed-length segmentation, the proposed method has a higher sensitivity and a better characterization in muscle fatigue detection.

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备注/Memo

备注/Memo:
【收稿日期】2020-02-19 【基金项目】兰州军区医药卫生科研课题（CLZ14JA05） 【作者简介】包其扬，助理工程师，研究方向：医疗设备维修、管理及临床应用，E-mail: 13909402983@163.com 【通信作者】王军霞，E-mail: 1473723812@qq.com
更新日期/Last Update: 2020-10-29