Noise reduction based on ICA decomposition and wavelet transform for the extraction of motor unit action potentials

Journal of Neuroscience Methods

Volumn 158, Issue 2, 2006, Pages 313-322

  Ren, Xiaomei ^a,b   Yan, Zhiguo ^a   Wang, Zhizhong ^a   Hu, Xiao ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b SHANXI UNIVERSITY   (China)

Author keywords

Amplitude threshold filtering (ATF); Electromyography (EMG); Independent component analysis (ICA); Motor unit action potential (MUAP); Myoelectric signal (MES); Power spectral density (PSD); Threshold estimate; Wavelet filtering

Indexed keywords

ADULT; ANALYTIC METHOD; ARTICLE; CONTROLLED STUDY; ELECTROMYOGRAM; FEMALE; HUMAN; INDEPENDENT COMPONENT ANALYSIS; MALE; MOTOR UNIT POTENTIAL; MYOELECTRICITY; NOISE REDUCTION; NORMAL HUMAN; PRIORITY JOURNAL; SIGNAL PROCESSING; SIGNAL TRANSDUCTION; WAVEFORM; WHITE NOISE;

ACTION POTENTIALS; ADULT; ALGORITHMS; COMPUTER SIMULATION; ELECTROMYOGRAPHY; FEMALE; HUMANS; MALE; MOTOR NEURONS; MUSCLE, SKELETAL; PRINCIPAL COMPONENT ANALYSIS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 33750940946     PISSN: 01650270     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2006.06.005     Document Type: Article

References (24)

1. Baikun W., Xin Z., Chunmei Y., and Yang G. Study on applying independent component analysis to remove blink artifacts and power noise in EEG. Acto Electron Sinica 31 (2003) 1571-1574
2. Christodoulou C.I., and Pattichis C.S. Unsupervised pattern recognition for the classification of EMG signals. IEEE Trans Biomed Eng 46 (1999) 169-178
3. Conforto S., D'Alessio T., and Pignatelli S. Optimal rejection of movement artifacts from myoelectric signals by means of a wavelet filtering procedure. J Electromyogr Kinesiol 9 (1999) 47-57
4. Conte L.R.L., Merletti R., and Sandri G.V. Hermite expansions of compact support waveforms: applications to myoelectric signals. IEEE Trans Biomed Eng 41 (1994) 1147-1159
5. Fang J., Agarwal G.C., and Shahani B.T. Decomposition of multiunit electromyographic signals. IEEE Trans Biomed Eng 46 (1999) 685-697
6. Farina D., Crosetti A., and Merletti R. A model for the generation of synthetic intramuscular EMG signals to test decomposition algorithms. IEEE Trans Biomed Eng 48 (2001) 66-77
7. Gazzoni M., Farina D., and Merletti R. A new method for the extraction and classification of single motor unit action potentials from surface EMG signals. J Neurosci Meth 136 (2004) 165-177
8. Gut R., and Moschytz G.S. High-precision EMG signal decomposition using communication techniques. IEEE Trans Signal Process 48 (2000) 2487-2494
9. Hyvärinen A. Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans Neural Network 10 (1999) 626-634
10. Hyvärinen A., and Oja E. Independent component analysis: algorithms and applications. Neural Network 13 (2000) 411-430
11. LeFever R.S., and DeLuca C.J. A procedure for decomposing the myoelectric signal into its constituent action potentials. Part I. Technique, theory, and implementation. IEEE Trans Biomed Eng bme-29 3 (1982) 149-157
12. McGill K.C., Cummins K.L., and Dorfman L.J. Automatic decomposition of the clinical electromyogram. IEEE Trans Biomed Eng BME-32 7 (1985) 470-477
13. Mewett D.T., Reynolds K.J., and Nazeran H. Reducing power line interference in digitized electromyogram recordings by spectrum interpolation. Med Biol Eng Comput 42 (2004) 524-531
14. Nakamura H., Yoshida M., Kotani M., Akazawa K., and Moritani T. The application of independent component analysis to the multi-channel surface electromyographic signals for separation of motor unit action potential trains. Part I. Measuring techniques. J Electromyogr Kinesiol 14 (2004) 423-432
15. Ortolan R.L., Mori R.N., Pereira R.R., Cabral C.M.N., Pereira J.C., and Cliquet A. Evaluation of adaptive/nonadaptive filtering and wavelet transform techniques for noise reduction in EMG mobile acquisition equipment. IEEE Trans Neural Syst Reh 11 (2003) 60-69
16. Pattichis C.S., Schizas C.N., and Middleton L.T. Neural network models in EMG diagnosis. IEEE Trans Biomed Eng 42 (1995) 486-496
17. Slawnych M., Laszlo C., and Hershler C. Motor unit estimates obtained using the new "MUESA" method. Muscle Nerve 19 (1996) 626-636
18. Stälberg E., Falck B., Sonoo M., Stälberg S., and Åström M. Multi-MUP EMG analysis-a two year experience in daily clinical work. Electroenceph Clin Neurophsiol 9 (1995) 145-154
19. Stashuk D. EMG signal decomposition: how can it be accomplished and used?. J Electromyogr Kinesiol 11 (2001) 151-173
20. Stashuk D., and Bruin H.D. Automatic decomposition of selective needle-detected myoelectric signals. IEEE Trans Biomed Eng 35 (1988) 1-10
21. Xiaomei R., Zhizhong W., and Xiao H. Independent component analysis and wavelet decomposition technique for the detection of motor unit action potentials. 27th annual international conference of the IEEE EMBS (2005)
22. Yuzhen C., Cheng C., Yong H., and Hongtao L. An improved denoise method based on independent component analysis to remove ECG noise in surface EMG signal. Signal Process (China) 19 (2003) 369-372
23. Zennaro D., Wellig P., Moschytz G.S., Läubli T., and Krueger H. A decomposition software package for the decomposition of long-term multi-channel electromyographic signals. 2001 Proceedings of the 23rd annual EMBS international conference (2001) 1070-1073
24. Zennaro D., Koch V.M., Moschytz G.S., and Läubli T. A software package for the decomposition of long-term multichannel EMG signals using wavelet coefficients. IEEE Trans Biomed Eng 50 (2003) 58-69