Medical Engineering & Physics
Volume 28, Issue 7 , Pages 694-709 , September 2006

Adaptive fuzzy k-NN classifier for EMG signal decomposition

  • Sarbast Rasheed

      Affiliations

    • Pattern Analysis and Machine Intelligence Lab, Department of Systems Design Engineering, University of Waterloo, Waterloo, Ont., Canada N2L 3G1
    • Corresponding Author InformationCorresponding author. Tel.: +1 519 8884567; fax: +1 519 7464791.
    • ,
  • Daniel Stashuk

      Affiliations

    • Pattern Analysis and Machine Intelligence Lab, Department of Systems Design Engineering, University of Waterloo, Waterloo, Ont., Canada N2L 3G1
    • ,
  • Mohamed Kamel

      Affiliations

    • Pattern Analysis and Machine Intelligence Lab, Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ont., Canada N2L 3G1

Received 26 July 2005 ,Revised 2 November 2005 ,Accepted 9 November 2005.

References 

  1. Basmajian JV, De Luca CJ. Muscles alive: their functions revealed by electromyography. 5th ed.. Baltimore, MD: Williams and Wilkins; 1985;
  2. Duda RO, Hart PE, Stork DG. Pattern classification. 2nd ed.. John Wiley & Sons; 2001;
  3. Fang J, Agarwal GC, Shahani BT. Decomposition of multiunit electromyogram signals. IEEE Trans Biomed Eng. 1999;46(6):685–697
  4. Hamilton-Wright A, Stashuk DW. Physiologically based simulation of clinical EMG signals. IEEE Trans Biomed Eng. 2005;52(2):171–183
  5. Hassoun MH, Wang C, Spitzer R. Nnerve: neural network extraction of repetitive vectors for electromyography—Part I: algorithm. IEEE Trans Biomed Eng. 1994;41(11):1039–1052
  6. Hassoun MH, Wang C, Spitzer R. Nnerve: neural network extraction of repetitive vectors for electromyography—Part II: performance analysis. IEEE Trans Biomed Eng. 1994;41(11):1053–1061
  7. Keller JM, Gray MR, Givens JA. A fuzzy k-nearest neighbor algorithm. IEEE Trans Syst Man Cybern. 1985;15(July/August (4)):580–585
  8. Kuncheva LI. Fuzzy classifier design. Studies in fuzziness and soft computing. Physica-Verlag; 2000;
  9. LeFever RS, De Luca CJ. A procedure for decomposing the myoelectric signal into its constituent action potentials—Part i: technique, theory, and implementation. IEEE Trans Biomed Eng. 1982;29(3):149–157
  10. De Luca CJ. Physiology and mathematics of myoelectric signals. IEEE Trans Biomed Eng. 1979;26(6):313–325
  11. Matthews PBC. Relationship pf firing intervals of human motor units to the trajectory of post-spike after-hyperpolarization and synaptic noise. J Physiol. 1996;492(2):597–628
  12. McGill KC. A method for quantitating the clinical electromyogram. Ph.D. dissertation. Stanford University, Stanford, CA, 1984.
  13. McGill KC, Cummins K, Dorfman LJ. Automatic decomposition of the clinical electromyogram. IEEE Trans Biomed Eng. 1985;32(7):470–477
  14. Medasani S, Kim J, Krishnapuram R. An overview of membership function generation techniques for pattern recognition. Int J Approximate Reason. 1998;19:391–417
  15. Nandedkar SD, Barkhaus PE, Charles A. Multi-motor unit action potential anamysis (MMA). Muscle Nerve. 1995;18:1155–1166
  16. Paoli GM. Estimating certainty in classification of motor unit action potentials. Master's thesis. University of Waterloo, Waterloo, Ont., Canada, 1993.
  17. Perkel D, Gerstein GL, Moore GP. Neural spike trains and stochastic point process—Part i. the single spike train. Biophys J. 1967;7:391–418
  18. Qu Y. Automatic clustering of motor unit action potentials using shape and time information. Master's thesis. University of Waterloo, Waterloo, Ont., Canada, 1993.
  19. Stashuk DW. Decomposition and quantitative analysis of clinical electromyographic signals. Med Eng Phys. 1999;21:389–404
  20. Stashuk DW. EMG signal decomposition: how can it be accomplished and used?. J Electromyogr Kinesiol. 2001;11:151–173
  21. Stashuk DW, de Bruin H. Automatic decomposition of selective needle-detected myoelectric signals. IEEE Trans Biomed Eng. 1988;35(1):1–10
  22. Stashuk DW, Paoli GM. Robust supervised classification of motor unit action potentials. Med Biol Eng Comput. 1998;36(1):75–82
  23. Stashuk DW, Qu Y. Adaptive motor unit action potential clustering using shape and time information. Med Biol Eng Comput. 1996;34(1):41–49
  24. Stashuk DW, Qu Y. Robust method for estimating motor unit firing-pattern statistics. Med Biol Eng Comput. 1996;34(1):50–57
  25. Usaui S, Amidror I. Digital low-pass differentiation for biological signal processing. IEEE Trans Biomed Eng. 1982;29(10):686–693
  26. Zennaro D, Wellig P, Koch VM, Moschytz GS, Laubli T. A software package for the decomposition of long-term multi-channel EMG signals using wavelet coefficients. IEEE Trans Biomed Eng. 2003;50(1):58–69

PII: S1350-4533(05)00243-2

doi: 10.1016/j.medengphy.2005.11.001

Medical Engineering & Physics
Volume 28, Issue 7 , Pages 694-709 , September 2006

Article Tools

* Image Usage & Resolution