期刊文献+

基于Hermite插值的小波模极大值重构滤波的肌电信号消噪方法 被引量:7

Hermite Interpolation-Based Wavelet Transform Modulus Maxima Reconstruction Algorithm's Application to EMG De-noising
下载PDF
导出
摘要 为了消除混杂在肌电信号中的噪声,该文提出了基于Hermite插值的小波模极大值重构滤波的肌电信号消噪方法。该方法先对肌电信号进行小波分解;其次,根据小波系数的奇异性,利用信号与噪声模极大值在小波尺度上的不同变化特性,分离出信号与噪声;再次,用Hermite插值法重构小波系数;最后从重构的小波系数恢复成去噪后的信号。实验结果表明,Hermite插值的小波模极大值重构能有效地去除噪声,提高信噪比,且保留了肌电信号的细节信息,为肌电信号的特征提取和模式识别创造了良好的条件。 In order to eliminate the noise mixed in EMG signal, a Hermite interpolation- based wavelet transform modulus maxima reconstruction algorithm is proposed. The obtained EMG signal is decomposed using the wavelet transform; the singularity and different properties of the signal and noise of the wavelet coefficient modulus under the different scales of wavelet transformation are used to separate the signal and noise; then the wavelet coefficients are reconstructed using Hermite interpolation; Finally, the de-noised signal is got by the wavelet reconstructed algorithm. Experiments show that, the method has good performance in removing noise, improving the signal-to-noise ratio and reserving the detailed information, which brings in favorable conditions to feature extraction and pattern recognition of EMG.
出处 《电子与信息学报》 EI CSCD 北大核心 2009年第4期857-860,共4页 Journal of Electronics & Information Technology
基金 国家自然科学基金(60705010) 浙江省科技计划(2007C23088)资助课题
关键词 肌电信号 小波变换 模极大值 HERMITE插值 EMG Wavelet transform Modulus maxima Hermite interpolation
  • 相关文献

参考文献10

二级参考文献51

  • 1郭健,孙炳楠.基于小波变换的桥梁健康监测多尺度分析[J].浙江大学学报(工学版),2005,39(1):114-118. 被引量:40
  • 2DelSys Incorporated, Surface Electromyography: Detection and Recording, 1996.
  • 3Edward A. Clancy, Estimation and Application of EMG Amplitude During Dynamic Contracfionss,IEEE Engineering in Medicine and Biology, 47-54, 2001.
  • 4Aapo Hyvarinen and Erkki Oja, Independent Component Analysis: A Tutorial, 1999.
  • 5Baratta R.V., Solomonow M., Zhou B.-H., Zhu M. (1998)Methods to reduce the variability of EMG power Spectrum estimates. J. Electromyogr. Kinesiol., 8: 279- 285.
  • 6A. Hyviirinen. Fast and Robust Fixed-Point Algorithms for Independent Component Analysis. IEEE Transactions on Neural Networks 10(3):626-634, 1999.
  • 7Serge H. Roy, Paolo Bonato,Marco Knaflitz,EMG assessment of back muscle function during cyclical lifting,Journal of Electromyography and Kinesiology 8 (1998)233-245.
  • 8杨福生.小波变换的工程分析与应用[M].北京:科学出版社,2000..
  • 9Z.Berman. The uniqueness questions of discrete wavelet maxima representation[R]. Tech. Rep. TR 91-84. Cent Univ. of Maryland,College Park, Apr, 1991.
  • 10S.G.Mallat Zero-crossings of wavelet transform[J]. IEEE trans.Inform. Theory, 1991, 37.

共引文献64

同被引文献93

  • 1杨鹏,刘作军,耿艳利,赵丽娜.智能下肢假肢关键技术研究进展[J].河北工业大学学报,2013,42(1):76-80. 被引量:33
  • 2张毅,代凌凌,罗元.基于SEMG控制的智能轮椅无障碍人机交互系统[J].华中科技大学学报(自然科学版),2011,39(S2):264-267. 被引量:14
  • 3加玉涛,罗志增.肌电信号特征提取方法综述[J].电子器件,2007,30(1):326-330. 被引量:30
  • 4胡广书.现代信号处理教程[M]. 北京: 清华大学出版社, 2011:377-381.
  • 5Ajoudani A, Tsagarakis N, and Bicchi A. Tele-impedance: teleoperation with impedance regulation using a body machine interface[J]. The International Journal of Robotics Research, 2012, 31(13): 1642-1656.
  • 6Naik G R, Kumar D K, and Arjunan S P. Towards classification of low-level finger movements using forearm muscle activation: a comparative study based on ICA and fractal theory[J]. International Journal of Biomedical Engineering and Technology, 2011, 6(2): 150-162.
  • 7Phinyomark A, Phukpattaranont P, and Limsakul C. Fractal analysis features for weak and single-channel upper-limb EMG signals[J]. Expert Systems with Applications, 2012, 39(12): 11156-11163.
  • 8Hu Xiao, Wang Zhi-zhong, and Ren Xia-mei. Classification of forearm action surface EMG signals based on fractal dimension[J]. Journal of Southcast University (English Edition), 2005, 21(3): 324-329.
  • 9Grassberger P and Procaccia I. Measuring the strangeness ofstrange attractors[J]. Physica D: Nonlinear Phenomena, 1983, 9(1): 189-208.
  • 10Kugiumtzis D. State space reconstruction parameters in the analysis of chaotic time series -- the role of the time window length[J]. Physica D: Nonlinear Phenomena, 1996, 95(1): 13 -28.

引证文献7

二级引证文献59

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部