Multiplicative multi-fractal modeling of electromyography signals for discerning neuropathic conditions.
In this paper, we present a new method for multi-scale analysis of electromyography signals based on an interesting fractal process known as multiplicative cascade multi-fractal. Using simulated needle electromyography signals, we show this method provides a means for discrimination of normal and neuropathic electromyography signals. We also present experimental results that show the new parameters, computed using multiplicative cascade multi-fractal modeling, are more robust than the conventional signal parameter, number of turns, in the presence of additive noise. Results of multiplicative cascade multi-fractal modeling are consistent with other multi-scale approaches; advantages and differences are high lighted.
Talebinejad
Mehran
M
Department of Electrical Engineering, McGill University, Canada. mehran.talebinejadmohammadi@mail.mcgill.ca
Chan
Adrian D C
AD
Miri
Ali
A
D004576:Electromyography / Q000379:methods*; D006801:Humans; D008962:Models, Theoretical; D009422:Nervous System Diseases / Q000175:diagnosis