Journal of Electromyography and Kinesiology
Volume 20, Issue 6 , Pages 1088-1096 , December 2010

Wavelet based correlation and coherence analysis reveals frequency dependent motor unit conduction velocity of the abductor pollicis brevis muscle

  • Vinzenz von Tscharner

      Affiliations

    • Human Performance Laboratory, University of Calgary, Calgary, Alberta, Canada
    • Corresponding Author InformationCorresponding author. Address: University of Calgary, Human Performance Laboratory, 2500 University Drive, Calgary, Alberta, Canada T2N 1N4. Tel.: +1 403 949 3714.
    • ,
  • Marina Barandun

      Affiliations

    • Department of Plastic and Reconstructive Surgery, University Hospital Basel, Switzerland

Received 19 July 2009 ,Revised 25 April 2010 ,Accepted 23 June 2010.

References 

  1. Arabadzhiev TI, Dimitrov GV, Dimitrova NA. The cross-correlation and phase-difference methods are not equivalent under noninvasive estimation of the motor unit propagation velocity. J Electromyogr Kinesiol. 2004;14(3):295–305
  2. Arabadzhiev TI, Dimitrov GV, Dimitrova NA. Simulation analysis of the ability to estimate motor unit propagation velocity non-invasively by different two-channel methods and types of multi-electrodes. J Electromyogr Kinesiol. 2003;13(5):403–415
  3. Barandun M, von Tscharner V, Meuli-Simmen C, Bowen V, Valderrabano V. Conduction velocity analysis of the abductor pollicis brevis muscle during early fatigue. J Electromyogr Kinesiol. 2009;19(1):65–74
  4. Broman H, Biloto G, De Luca CJ. A note on the noninvasive estimation of muscle fiber conduction velocity. IEEE Trans Biomed Eng. 1985;32:341–344
  5. Cescon C, Rebecchi P, Merletti R. Effect of electrode array position and subcutaneous tissue thickness on conduction velocity estimation in upper trapezius muscle. J Electromyogr Kinesiol. 2008;18(4):628–636
  6. Conforto S, Alessio TD, Pignatelli S. Optimal rejection of movement artefacts from myoelectric signals by means of a wavelet filtering procedure. J Electromyogr Kinesiol. 1999;9:47–57
  7. Dimitrova NA, Dimitrov GV. Interpretation of EMG changes with fatigue: facts, pitfalls, and fallacies. Journal of Electromyography and Kinesiology. 2003;13:13–36
  8. Farina D, Cescon C, Merletti R. Influence of anatomical, physical, and detection-system parameters on surface EMG. Biol Cybern. 2002;86:445–456
  9. Farina D. Counterpoint: spectral properties of the surface EMG do not provide information about motor unit recruitment and muscle fiber type. J Appl Physiol. 2008;105(5):1673–1674
  10. Klein A, Sauer T, Jedynak A, Skrandies W. Conventional and wavelet coherence applied to sensory-evoked electrical brain activity. IEEE Trans Biomed Eng. 2006;53(2):266–272
  11. Kulick MI, Gordillo G, Javidi T, Kilgore ES, Newmayer WL. Long-term analysis of patients having surgical treatment for carpal tunnel syndrome. J Hand Surg. 1986;11:59–66
  12. Kuiken TA, Lowery MM, Stoykov NS. The effect of subcutaneous fat on myoelectric signal amplitude and cross-talk. Prosthet Orthot Int. 2003;27(1):48–54
  13. MacDermid JC, Wessel J. Clinical diagnosis of carpal tunnel syndrome: a systematic review. J Hand Ther. 2004;17:309–319
  14. Ramsay JO, Silverman BW. Functional data analysis. New York: Springer-Verlag; 1997;
  15. Rosenberg JR, Amjad AM, Breeze P, Brillinger DR, Halliday DM. The Fourier approach to the identification of functional coupling between neuronal spike trains. Prog Biophys Mol Biol. 1989;53:1–31
  16. Soo Y, Sugi M, Yokoi H, Arai T, Nishino M, Kato R, et al. Estimation of handgrip force using frequency-band technique during fatiguing muscle contraction. J Electromyogr Kinesiol 2009; doi:10.1016/j.jelekin.2009.08.008.
  17. von Tscharner V. In:  Nigg B,  Herzog W editor. Biomechanics of musculo-skeletal system. third ed.. England: John Wiley and Sons Ltd.; 2007;p. 409–452
  18. von Tscharner V, Goepfert B. Estimation of the interplay between groups of fast and slow muscle fibers of the tibialis anterior and gastrocnemius muscle while running. J Electromyogr Kinesiol. 2006;16(2):188–197
  19. von Tscharner V. Time-frequency and principal-component methods for the analysis of EMGs recorded during a mildly fatiguing exercise on a cycle ergometer. J Electromyogr Kinesiol. 2002;12(6):479–492
  20. von Tscharner V. Intensity analysis in time-frequency space of surface myoelectric signals by wavelets of specified resolution. J Electromyogr Kinesiol. 2000;10:433–445
  21. von Tscharner V, Nigg BM. Point: spectral properties of the surface EMG can characterize/do not provide information about motor unit recruitment strategies and muscle fiber type. J Appl Physiol. 2008;105(5):1671–1673
  22. Wakeling JM, Kaya M, Temple GK, Johnston IA, Herzog W. Determining patterns of motor recruitment during locomotion. J Exp Biol. 2002;205(Pt 3):359–369

PII: S1050-6411(10)00093-3

doi: 10.1016/j.jelekin.2010.06.004

Journal of Electromyography and Kinesiology
Volume 20, Issue 6 , Pages 1088-1096 , December 2010

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