Development of electromyography signal signature for forearm muscle

I. Elamvazuthi, Zulika Zulkifli, Zulfiqar Ali, M. K.A.Ahamed Khan, S. Parasuraman, M. Balaji, M. Chandrasekaran

Research output: Chapter in Book/Report/Conference proceedingConference PaperOther

9 Citations (Scopus)

Abstract

Electromyography (EMG) measures muscle response or electrical activity in response to a nerve's stimulation of the muscle. EMG is generally acquired through surface and needle or wire electrodes. The needle or wire electrodes are usually used by clinicians in a clinical setting. This paper concentrates on surface electromyography (sEMG) signal that is acquired in a research laboratory since sEMG is increasingly being recognized as the gold standard for the analysis of muscle activation. The sEMG can utilized for establishing signal signature for forearm muscles that becomes an important input in development of rehabilitative devices. This paper discusses the establishment of sEMG signal signature of female and male subjects for forearm muscles such as extensor carpi radialis, flexor carpi radialis, palmaris longus and pronator teres based on movements such as wrist extension and flexion, hand open and close, and forearm supination and pronation. This was achieved through the use of Butterworth Bessel, Elliptic and Chebyshev filters. The sEMG signal signature could be useful in the development of rehabilitation device of upper extremities.

Original languageEnglish
Title of host publicationIEEE International Symposium on Robotics and Intelligent Sensors, IEEE IRIS 2015
Pages229-234
Number of pages6
Volume76
DOIs
Publication statusPublished - 2015
EventIEEE International Symposium on Robotics and Intelligent Sensors 2015 - Langkawi, Malaysia
Duration: 18 Oct 201520 Oct 2015
https://www.sciencedirect.com/journal/procedia-computer-science/vol/76/suppl/C (Proceedings)

Publication series

NameProcedia Computer Science
PublisherElsevier
ISSN (Print)1877-0509

Conference

ConferenceIEEE International Symposium on Robotics and Intelligent Sensors 2015
Abbreviated titleIRIS 2015
Country/TerritoryMalaysia
CityLangkawi
Period18/10/1520/10/15
Internet address

Keywords

  • Electromyography
  • filtering
  • forearm muscle
  • rehabilitation
  • signal signature

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