| 应用小波变换和ICA方法的肌电信号分解 |
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| 引用本文： | Ren Xiaomei,任小梅,王志中,胡晓. 应用小波变换和ICA方法的肌电信号分解[J]. 数据采集与处理, 2006, 21(3): 272-276 |
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| 作者姓名： | Ren Xiaomei 任小梅 王志中 胡晓 |
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| 作者单位： | 上海交通大学生物医学工程系,上海,200030;上海交通大学生物医学工程系,上海,200030;华南师范大学激光生命科学研究所,广州,510631 |
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| 基金项目： | 国家重点基础研究发展计划(973计划) |
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| 摘 要： | 基于单通道、短时真实肌电（EMG）记录和模拟EMG信号，提出一种改进的肌电信号分解方法。首先应用小波滤波、硬阈值估计等方法去除背景噪声和白噪声，并将独立成分分析（ICA）方法和小波滤波方法相结合去除工频干扰信号，然后再进行幅度滤波，从而提高了系统的速度和强健性。在运动单元动作电位（MUAP）聚类以及从原始信号中去除已识别的MUAP波形等方面也进行了改进。与已有的EMG分解方法相比，本文方法更快速、稳定。
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| 关 键 词： | 肌电信号分解 独立成分分析(ICA) 小波滤波 阈值估计 |
| 文章编号： | 1004-9037（2006）03-0272-05 |
| 收稿时间： | 2005-09-26 |
| 修稿时间： | 2006-01-22 |
EMG Signal Decomposition Based on Wavelet Transform and ICA Method |
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| Ren Xiaomei. EMG Signal Decomposition Based on Wavelet Transform and ICA Method[J]. Journal of Data Acquisition & Processing, 2006, 21(3): 272-276 |
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| Authors: | Ren Xiaomei |
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| Affiliation: | 1. Department of Biomedical Engineering, Shanghai Jiaotong University, Shanghai, 200030, China; 2. Laser Life Science Institute, South China Normal University, Guangzhou, 510631, China |
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| Abstract: | An effective method for electromyography(EMG) signal decomposition is deve-loped based on the real EMG recording of single-channel short period from normal subjects and artificial generated EMG signals.Firstly,this paper utilizes the wavelet filtering and the threshold estimation in the wavelet transform to reduce the noise in EMG signals and to detect motor unit action potentials(MUAP).Then,the power line interference is removed from EMG recording by combining the independent component analysis(ICA) and the wavelet filter method.Finally,the ICA method is used to subtract all these MUAP spikes from original EMG signals.Compared with existing EMG decomposition methods,the method is fast and reliable. |
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| Keywords: | EMG signal decomposition independent component analysis(ICA) wavelet(filtering ) threshold estimation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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