title: Multiplicative multi-fractal modeling of electromyography signals for discerning neuropathic conditions.
abstract: 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.
authors: Department of Electrical Engineering, McGill University, Canada. mehran.talebinejadmohammadi@mail.mcgill.ca
authors: Mehran
authors: M
authors: Talebinejad
authors: Adrian D C
authors: AD
authors: Chan
authors: Ali
authors: A
authors: Miri
mesh_terms: D004576:Electromyography / Q000379:methods*; D006801:Humans; D008962:Models, Theoretical; D009422:Nervous System Diseases / Q000175:diagnosis