• Rebecca B J Beck, Caroline J Houtman, Mark J O'Malley, Madeleine M Lowery, and Dick F Stegeman.
• Department of Electronic and Electrical Engineering, University College Dublin, Dublin 4, Ireland. rebecca.beck@ucd.ie
• IEEE Trans Biomed Eng. 2005 Apr 1; 52 (4): 622-9.

AbstractThe speed of propagation of an action potential along a muscle fiber, its conduction velocity (CV), can be used as an indication of the physiological or pathological state of the muscle fiber membrane. The motor unit action potential (MUAP), the waveform resulting from the spatial and temporal summation of the individual muscle fiber action potentials of that motor unit (MU), propagates with a speed referred to as the motor unit conduction velocity (MUCV). This paper introduces a new algorithm, the MU tracking algorithm, which estimates MUCVs and MUAP amplitudes for individual MUs in a localized MU population using SEMG signals. By tracking these values across time, the electrical activity of the localized MU pool can be monitored. An assessment of the performance of the algorithm has been achieved using simulated SEMG signals. It is concluded that this analysis technique enhances the suitability of SEMG for clinical applications and points toward a future of noninvasive diagnosis and assessment of neuromuscular disorders.

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