Extraction of motor unit action potentials from electromyographic signals through generative topographic mapping

Journal of the Franklin Institute

Volumn 344, Issue 3-4, 2007, Pages 154-179

  Andrade, Adriano O ^a   Nasuto, Slawomir J ^b   Kyberd, Peter ^c  

^a FEDERAL UNIVERSITY OF UBERLÂNDIA   (Brazil)

^b UNIVERSITY OF READING   (United Kingdom)

^c UNIVERSITY OF NEW BRUNSWICK   (Canada)

Author keywords

Cluster analysis; Electromyography; EMG decomposition; Generative topographic mapping; Motor unit action potentials

Indexed keywords

CLUSTER ANALYSIS; DISEASES; ELECTRODES; MUSCULOSKELETAL SYSTEM; TOPOGRAPHY;

EMG DECOMPOSITION; GENERATIVE TOPOGRAPHIC MAPPING; MOTOR UNIT ACTION POTENTIALS;

ELECTROMYOGRAPHY;

EID: 33947527059     PISSN: 00160032     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfranklin.2006.10.006     Document Type: Article

References (35)

1. Barwick D.D. Clinical electromyography. In: Walton S.J. (Ed). Disorders of Voluntary Muscle (1981), Churchill Livingstone, New York 952-975
2. Pullman S.L., Goodin D.D., Marquinez A.I., Tabbal S., and Rubin M. Clinical utility of surface EMG: report of the therapeutics and technology assessment subcommittee of the American academy of neurology. Neurology 55 2 (2000) 171-177
3. Cram J.R. The history of surface electromyography. Appl. Psychophys. Biofeedback 28 2 (2003) 81-91
4. Cram J.R., Kasman G.S., and Holtz J. Introduction to Surface Electromyography. first ed. (1998), Aspen Publishers, Gaithersburg, MD
5. Pattichis C.S., Schofield I., Merletti R., Parker P.A., and Middleton L.T. Introduction to this special issue intelligent data analysis in electromyography and electroneurography. Med. Eng. Phys. 21 6-7 (1999) 379-388
6. Stashuk D. EMG signal decomposition: how can it be accomplished and used?. J. Electromyogr. Kinesiology 11 3 (2001) 151-173
7. Stashuk D., and Paoli G.M. Robust supervised classification of motor unit action potentials. Med. Biol. Eng. Comput. 36 (1998) 75-82
8. A. O. Andrade, "Decomposition and analysis of electromyographic signals," Ph.D. Thesis, University of Reading, Reading, UK, 2005.
9. LeFever R.S., and De Luca C.J. A procedure for decomposing the myoelectric signal into its constituent action potentials-part I: technique, theory, and implementation. IEEE Trans. Biomed. Eng. 29 3 (1982) 149-157
10. Mambrito B., and De Luca C.J. A technique for the detection, decomposition and analysis of the EMG signal. Electroencephalogr. Clin. Neurophysiol. 58 (1984) 175-188
11. 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
12. Joynt R.L., Erlandson R.F., Wu S.J., and Wang C.M. Electromyography interference pattern decomposition. Arch. Phys. Med. Rehabil. 72 8 (1991) 567-572
13. Stashuk D.W., and Naphan R.K. Probabilistic inference-based classification applied to myoelectric signal decomposition. IEEE Trans. Biomed. Eng. 39 4 (1992) 346-355
14. Hassoun M.H., Wang C., and Spitzer A.R. NNERVE: neural network extraction of repetitive vectors for electromyography-part I: algorithm. IEEE Trans. Biomed. Eng. 41 11 (1994) 1039-1051
15. Etawil H., and Stashuk D. Resolving superimposed motor unit action potentials. Med. Biol. Eng. Comput. 34 1 (1996) 33-40
16. Christodoulou C.I., and Pattichis C.S. Unsupervised pattern recognition for the classification of EMG signals. IEEE Trans. Biomed. Eng. 46 2 (1999) 169-199
17. Zennaro D., Wellig P., Koch V.M., Moschytz G.S., and Laubli T. A software package for the decomposition of long-term multichannel EMG signals using wavelet coefficients. IEEE Trans. Biomed. Eng. 50 1 (2003) 58-69
18. Basmajian J.V., and DeLuca C.J. Muscles Alive: Their Functions Revealed by Electromyography. fifth ed. (1985), Williams and Wilkins, Baltimore, MD
19. Lewicki M.S. A review of methods for spike sorting: the detection and classification of neural action potentials. Comput. Neural Syst. 9 (1998) R53-R78
20. J.F.M. Svensen, GTM: the generative topographic mapping, Ph.D. Dissertation, Aston University, Birmingham, UK, 1998.
21. Bishop C.M., Svensen M., and Willians C.K.I. The generative topographic mapping. Neural Comput. 10 1 (1998) 215-234
22. Bishop C.M., and Svensen M. Developments of the generative topographic mapping. Neurocomputing 21 (1998) 203-224
23. A. O. Andrade, S. Nasuto, P. Kyberd, An automatic system for clustering and visualization of motor unit action potentials based on the generative topographic mapping, in: A.K. Nandi (Ed.), The Third IEE International Seminar on Medical Applications of Signal Processing, vol. 1, IEE, The IEE Savoy Place, London, UK, 2005, pp. 125-130.
24. Andrade A.O., Nasuto S., Kyberd P., and Sweeney-Reed C. Generative topographic mapping applied to clustering and visualization of motor unit action potentials. Biosystems 82 3 (2005) 273-284
25. Andrade A.O., Nasuto S., and Kyberd P. EMG signal filtering based on empirical mode decomposition. Biomed. Signal Process. Control 1 1 (2006) 44-55
26. Huang N.E., Shen Z., Long S.R., Wu M.C., Shih H.H., Zheng Q., Yen N.-C., Tung C.C., and Liu H.H. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc. R. Soc. London 454 (1998) 903-995
27. Donoho D.L. De-noising by soft-thresholding. IEEE Trans. Inform. Theory 41 3 (1995) 613-627
28. Debnath L., and Mikusinski P. Introduction to Hilbert Spaces with applications. second ed. (1999), Academic Press, San Diego, CA
29. Lohninger H. Teach/Me Data Analysis (1999), Springer, Berlin, Germany
30. Ritter H. Self-organizing feature maps. In: Arbib M.A. (Ed). The Handbook of Brain and Neural Networks. first ed. (2001), MIT Press, Cambridge, MA 1005-1010
31. Farina D., Colombo R., Merletti R., and Olsen H.B. Evaluation of intra-muscular EMG signal decomposition algorithms. J. Electromyogr. Kinesiology 11 (2001) 175-187
32. McGill K.C. Surface electromyogram modelling. Med. Biol. Eng. Comput. 42 (2004) 446-454
33. Morris T. Computer Vision and Image Processing. first ed. (2004), Palgrave Macmillan, New York
34. Snider R.K., and Bonds A.B. Classification of non-stationary neural signals. J. Neurosci. Methods 84 (1998) 155-166
35. Sharma S. Applied Multivariate Techniques (1996), Wiley, Cambridge, MA