[1]刘若汐,饶家声,魏瑞晗,等.恒河猴表面肌电信号小波去噪的复合评价指标[J].中国医学物理学杂志,2020,37(9):1169-1174.[doi:10.3969/j.issn.1005-202X.2020.09.017]
 LIU Ruoxi,RAO Jiasheng,WEI Ruihan,et al.A composite evaluation indicator of wavelet denoising in surface electromyography of rhesusmonkey[J].Chinese Journal of Medical Physics,2020,37(9):1169-1174.[doi:10.3969/j.issn.1005-202X.2020.09.017]
点击复制

恒河猴表面肌电信号小波去噪的复合评价指标()
分享到:

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
37
期数:
2020年第9期
页码:
1169-1174
栏目:
医学人工智能
出版日期:
2020-09-25

文章信息/Info

Title:
A composite evaluation indicator of wavelet denoising in surface electromyography of rhesus monkey
文章编号:
1005-202X(2020)09-1169-06
作者:
刘若汐1饶家声12魏瑞晗1赵璨23杨朝阳24李晓光124
1. 北京航空航天大学生物与医学工程学院,生物材料与神经再生北京市重点实验室,北京100083;2. 北京航空航天大学生物医 学工程高精尖创新中心,生物材料与神经再生北京市国际科技合作基地,北京100083;3. 北京航空航天大学仪器科学与光电工 程学院,北京100083;4. 首都医科大学基础医学院神经生物学系,北京100069
Author(s):
LIU Ruoxi1 RAO Jiasheng1 2 WEI Ruihan1 ZHAO Can2 3 YANG Zhaoyang2 4 LI Xiaoguang1 2 4
1. Beijing Key Laboratory for Biomaterials and Neural Regeneration, School of Biological Science and Medical Engineering, Beihang University, Beijing 100083, China 2. Beijing International Cooperation Bases for Science and Technology on Biomaterials and Neural Regeneration, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing 100083, China 3. School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100083, China 4. Department of Neurobiology, School of Basic Medicine, Capital Medical University, Beijing 100069, China
关键词:
恒河猴表面肌电信号去噪变异系数评价指标
Keywords:
rhesus monkey surface electromyography denoising coefficient of variation evaluation indicator
分类号:
R318
DOI:
10.3969/j.issn.1005-202X.2020.09.017
文献标志码:
A
摘要:
恒河猴表面肌电信号(sEMG)的去噪处理对于恒河猴运动学研究具有重要意义,其效果直接影响对恒河猴运动功 能评价的准确度。针对该类sEMG去噪效果综合评价法缺失的问题,提出一种通过变异系数定权确定的复合评价指标。 首先计算去噪信号的信噪比、均方根误差、平滑度、互相关系数等原始指标,并进行正向化、均值化处理,再利用变异系数 计算指标权重,将预处理后的原始指标加权组合为复合指标。进一步的仿真实验和实际实验数据计算表明,本文构建的 复合评价指标敏感性为1.72%±0.02%、准确性为83.64%,均显著高于现有指标的敏感性(1.04%±0.01%)和准确性 (75.76%),能够较好地反映恒河猴sEMG小波去噪效果,在恒河猴的运动行为研究中具有一定的应用价值。
Abstract:
The denoising of the surface electromyography (sEMG) of rhesus monkey has great significance for the kinematics research, and its effect directly affects the accuracy of motor function evaluation. Aiming at the problem of the lack of method for comprehensively evaluating sEMG denoising effect, a composite evaluation indicator determined by the coefficient of variation is proposed. The original indicators such as signal-to-noise ratio, root-mean-square error, smoothness and cross correlation coefficient were firstly calculated, and then were processed with positive management and averaging. Subsequently, the coefficient of variation was used to calculate the weights, and the preprocessed original indicators were combined into a composite indicator. Further simulation experiments and actual experimental data calculations show that the composite indicator proposed in this study achieves a sensitivity of 1.72%±0.02% and an accuracy of 83.64%, which are significantly higher than the sensitivity (1.04%±0.01%) and the accuracy (75.76%) of existing indicator. The proposed composite indicator which can be used to better represent the wavelet denoising effect has certain application value in the study of the behavior of rhesus monkeys.

相似文献/References:

[1]吴志敏,杜佳乐,乔晓艳.经穴位电刺激下的表面肌电信号特征分析[J].中国医学物理学杂志,2015,32(01):77.[doi:10.3969/j.issn.1005-202X.2015.01.019]
[2]陈文敏,肖玲玲,李慧慧,等. 单侧痛腰椎间盘突出症的表面肌电信号特征[J].中国医学物理学杂志,2017,34(10):1022.[doi:DOI:10.3969/j.issn.1005-202X.2017.10.011]
 [J].Chinese Journal of Medical Physics,2017,34(9):1022.[doi:DOI:10.3969/j.issn.1005-202X.2017.10.011]
[3]雷建超,刘栋博,房玉,等.基于表面肌电信号的性别差异性手势识别[J].中国医学物理学杂志,2020,37(3):337.[doi:DOI:10.3969/j.issn.1005-202X.2020.03.016]
 LEI Jianchao,LIU Dongbo,FANG Yu,et al.Recognition of hand gestures with gender differences based on surface electromyographic signals[J].Chinese Journal of Medical Physics,2020,37(9):337.[doi:DOI:10.3969/j.issn.1005-202X.2020.03.016]
[4]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.[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(9):1302.[doi:DOI:10.3969/j.issn.1005-202X.2020.10.015]
[5]冯凯,董秀成,刘栋博.基于经验模态分解-小波包变换的表面肌电信号手势识别[J].中国医学物理学杂志,2021,38(4):461.[doi:DOI:10.3969/j.issn.1005-202X.2021.04.013]
 FENG Kai,DONG Xiucheng,LIU Dongbo.Empirical mode decomposition and wavelet packet transform applied to surface EMG signal for hand gesture recognition[J].Chinese Journal of Medical Physics,2021,38(9):461.[doi:DOI:10.3969/j.issn.1005-202X.2021.04.013]
[6]周明娟,王语园,王田戈,等.针对微弱表面肌电信号的采集电路设计[J].中国医学物理学杂志,2021,38(5):625.[doi:DOI:10.3969/j.issn.1005-202X.2021.05.019]
 ZHOU Mingjuan,WANG Yuyuan,WANG Tiange,et al.Design of acquisition circuit for weak surface electromyography signals[J].Chinese Journal of Medical Physics,2021,38(9):625.[doi:DOI:10.3969/j.issn.1005-202X.2021.05.019]
[7]张夏丰,阚秀,曹乐,等.基于肌电信号与肌肉形变信号的手语识别[J].中国医学物理学杂志,2021,38(11):1392.[doi:DOI:10.3969/j.issn.1005-202X.2021.11.014]
 ZHANG Xiafeng,KAN Xiu,CAO Le,et al.Sign language recognition based on electromyogram signal and muscle deformation signal[J].Chinese Journal of Medical Physics,2021,38(9):1392.[doi:DOI:10.3969/j.issn.1005-202X.2021.11.014]
[8]张建华,王豪,李克祥,等.基于KPCA的膝关节多模式连续运动估计[J].中国医学物理学杂志,2023,40(6):742.[doi:DOI:10.3969/j.issn.1005-202X.2023.06.012]
 ZHANG Jianhua,WANG Hao,LI Kexiang,et al.KPCA-based continuous motion estimation of knee joint in multiple motion modes[J].Chinese Journal of Medical Physics,2023,40(9):742.[doi:DOI:10.3969/j.issn.1005-202X.2023.06.012]
[9]张思河,曹乐,王金玮,等.基于表面肌电信号的BiLSTM-SA双臂肌力估计[J].中国医学物理学杂志,2023,40(11):1383.[doi:DOI:10.3969/j.issn.1005-202X.2023.11.011]
 ZHANG Sihe,CAO Le,WANG Jinwei,et al.BiLSTM-SA model for muscle strength estimation from sEMG[J].Chinese Journal of Medical Physics,2023,40(9):1383.[doi:DOI:10.3969/j.issn.1005-202X.2023.11.011]

备注/Memo

备注/Memo:
【收稿日期】2020-03-19 【基金项目】国家自然科学基金(31970970,31900980,31730030,31650001,31670988,31320103903,31771053);国家重点研发计划(2017YFC1104001, 2017YFC1104002);中国博士后科学基金(2018M640046);北京市自然科学基金(KZ201810025030,7194286);北京市科技计划 (Z181100001818007);中央高校基本科研业务费专项资金(YWF-19-BJ-J-282) 【作者简介】刘若汐,硕士,主要研究方向:人体行为工程与康复工程,E-mail: liuruoxi@buaa.edu.cn 【通信作者】饶家声,博士,讲师,主要研究方向:生物医学信息及仪器医学数据处理技术等,E-mail: raojschina@126.com;杨朝阳,博士,教授,主 要研究方向:组织工程等,E-mail: wack_lily@163.com;李晓光,博士,教授,主要研究方向:组织工程与再生医学等,E-mail: lxgchina@ sina.com
更新日期/Last Update: 2020-09-25