A study on surface EMG generation model and its extraction

Author

Zou, Ling ; Ma, Xiaojuan ; Zhou, Tiantong ; Ma, Zhenghua

Author_Institution

Sch. of Inf. & Sci. & Eng., Changzhou Univ., Changzhou, China

Volume

2

fYear

2011

fDate

15-17 Oct. 2011

Firstpage

908

Lastpage

912

Abstract

A surface electromyography (sEMG) signal model is established and extracted from noisy background. Firstly, single fiber action potential (SFAP), motor unit action potential (MUAP) and motor unit action potential train (MUAPT) are simulated based on the tripolar signal source model, and then the sEMG is obtained. Secondly, the simulated sEMG signal is extracted from the mixed signals that consists of white noises, power frequency interference signal and electrocardio signal by independent component analysis (ICA) algorithms, and the most effective signal decomposition method Informax is chosen. It will lay the foundation for further decomposing the signals into single MUAP.

Keywords

electromyography; independent component analysis; medical signal processing; neurophysiology; signal sources; white noise; ICA algorithm; MUAPT; electrocardio signal; independent component analysis; motor unit action potential train; noisy background; power frequency interference signal; signal decomposition method Informax; simulated sEMG signal; single MUAP; single fiber action potential; surface EMG generation model; surface electromyography signal model; tripolar signal source model; white noise; Biological system modeling; Electric potential; Electromyography; Firing; Mathematical model; Muscles; Recruitment; Independent Component Analysis; Motor Unit Action Potential; Recruitment and Firing; sEMG Simulation;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Informatics (BMEI), 2011 4th International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-9351-7

Type

conf

DOI

10.1109/BMEI.2011.6098391

Filename

6098391