Decomposition of electromyogram long-term recordings

Author

Wellig, Peter ; Moschytz, George S. ; Läubli, Thomas

Author_Institution

Signal & Inf. Process. Lab., Swiss Fed. Inst. of Technol., Zurich, Switzerland

Volume

1

fYear

1999

fDate

1999

Abstract

In order to find the mechanisms responsible for the development of chronic neck pain caused by repetitive finger or arm movements, the long-term activation of motor units need to be studied. This requires intramuscular EMG long-term recordings. However, existing electromyogram (EMG signal) decomposition algorithms are restricted to short registration periods. In this paper, we present a decomposition algorithm capable of decomposing long-term recordings using discriminant time-frequency atoms

Keywords

electromyography; feature extraction; medical signal processing; pattern clustering; signal classification; time-frequency analysis; wavelet transforms; chronic neck pain; clustering techniques; discriminant time-frequency atoms; electromyogram long-term recordings; local discriminant basis algorithm; long-term activation; motor unit activation; repetitive arm movements; repetitive finger movements; signal decomposition algorithm; supervised classification; unsupervised classification; wavelet features; Clustering algorithms; Electromyography; Information processing; Muscles; Neck; Physiology; Recruitment; Shape measurement; Signal processing; Time frequency analysis;

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.1999.802656

Filename

802656