Simulation Analysis on the MUAPs Classification Using a Combined Detection Method

Author

Li, Qiang ; Yang, Ji-Hai

Author_Institution

Sch. of Inf. Eng., Southwest Univ. of Sci. & Technol., Mianyang, China

fYear

2010

fDate

18-20 June 2010

Firstpage

1

Lastpage

4

Abstract

For exploring the recognition performance of MUAPs, using the synthesized signal, the candidate MUAPs were detected by the combined method of continuous wavelet transform and hypothesis testing, the primary clustering of MUAPs was done by the fuzzy k-means algorithm, and the superimposed waveforms were decomposed by the modeling approach. The experimental results showed that the simulated MUAPs could be correctly extracted and classified by the proposed strategy.

Keywords

biomechanics; electromyography; fuzzy set theory; medical signal detection; medical signal processing; signal classification; wavelet transforms; EMG; MUAP classification; combined detection method; continuous wavelet transform; fuzzy k-means algorithm; hypothesis testing; motor unit action potentials; primary clustering; superimposed waveforms; Analytical models; Clustering algorithms; Continuous wavelet transforms; Electromyography; Pattern recognition; Signal analysis; Signal resolution; Source separation; Testing; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on

Conference_Location

Chengdu

ISSN

2151-7614

Print_ISBN

978-1-4244-4712-1

Electronic_ISBN

2151-7614

Type

conf

DOI

10.1109/ICBBE.2010.5518030

Filename

5518030