Spectrum of the nonstationary electromyographic signal modelled with integral pulse frequency modulation and its application to estimating neural drive information.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology

PubMedID: 18619856

Jiang N, Parker PA, Englehart KB. Spectrum of the nonstationary electromyographic signal modelled with integral pulse frequency modulation and its application to estimating neural drive information. J Electromyogr Kinesiol. 2009;19(4):e267-79.
The spectrum of nonstationary electromyographic signal (EMG) is investigated, from which the error for neural drive information estimation from nonstationary EMG is studied in terms of signal-to-noise ratio (SNR), in analytical, numerical simulation, and experimental work. The signal refers to the neural drive information embedded within the nonstationary EMG, and noise refers to other portions of EMG that induce error in the estimation. The analytical expressions for the SNRs of force-modulated EMG with both single and multiple motor units (MU) are derived based on a sinusoidal integral pulse frequency modulation (IPFM) model. It is shown that the previously developed SNR expressions for stationary (unmodulated) EMG are special cases of the formulas presented here. The SNR results obtained from numerical simulated EMG agree very well with the analytical result. Results from nonstationary (modulated) surface EMG obtained from seven subjects also match the analytical and simulation results reasonably well. The results obtained from this work establish an analytical framework in studying and estimating the neural drive information contained in the EMG in the context of anisotonic and isometric contractions. Through the analytical study, the effects of different physiological parameters are identified, thus providing theoretical guidelines for developing advanced signal processing methods for nonstationary EMG in applications such as prosthesis control.