Decomposition of low force, simulated EMG using wavelets

Author

Roberson, D.J. ; Rymer, W.Z.

Author_Institution

Sensory Motor Performance Program, Rehabilitation Inst. of Chicago, IL, USA

Volume

1

fYear

1999

fDate

1999

Abstract

Decoding the EMG signal could provide insight into the number and firing frequencies of the individual motoneurons innervating a particular muscle. An EMG signal was generated to approximate 5% maximum force generated. A custom wavelet was applied using a continuous wavelet transform. The coefficients generated were then compared with the number of action potentials used to generate the EMG. The results are encouraging

Keywords

correlation methods; electromyography; medical signal processing; signal classification; wavelet transforms; Hodgkin-Huxley equation; continuous wavelet transform; custom wavelet; low force simulated EMG; motoneuron information; motor unit recruitment; neural command signal; number of action potentials; signal decomposition; Continuous wavelet transforms; Displays; Electromyography; Force sensors; Frequency; Neurons; Shape; Signal generators; Wavelet coefficients; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint

Conference_Location

Atlanta, GA

ISSN

1094-687X

Print_ISBN

0-7803-5674-8

Type

conf

DOI

10.1109/IEMBS.1999.802654

Filename

802654