Decomposition of surface EMG signals using non-linear LMS optimisation of higher-order cumulants

Author

Plévin, Eric ; Zazula, Damjan

Author_Institution

Ecole Centrale de Nantes, France

fYear

2002

fDate

2002

Firstpage

149

Lastpage

154

Abstract

Deals with the problem of decomposition of surface electromyograms (SEMG). According to the physiological facts, a multiple-input multiple-output (MIMO) is used. The measured signals are taken as the channel responses corresponding to the motor-unit action potentials (MUAPs) convolution by the innervation pulse trains. The decomposition is based on the third-order cumulants whose values enter as coefficients of nonlinear system of equations. The system is solved by nonlinear least mean square (LMS) optimisation. Synthetic SEMG signals from a MIMO(2,3) with additive Gaussian noise with SNRs of 10 and 0 dB prove that a successful multichannel decomposition is possible also in very noisy environments.

Keywords

electromyography; higher order statistics; least mean squares methods; optimisation; additive Gaussian noise; channel responses; convolution; higher-order cumulants; innervation pulse trains; motor-unit action potentials; multichannel decomposition; multiple-input multiple-output; nonlinear least mean square optimisation; surface EMG signals; synthetic signals; third-order cumulants; very noisy environments; Additive noise; Convolution; Electromyography; Gaussian noise; Least squares approximation; MIMO; Nonlinear equations; Nonlinear systems; Pulse measurements; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer-Based Medical Systems, 2002. (CBMS 2002). Proceedings of the 15th IEEE Symposium on

ISSN

1063-7125

Print_ISBN

0-7695-1614-9

Type

conf

DOI

10.1109/CBMS.2002.1011369

Filename

1011369