Full metadata
Title
Isometric and dynamic contraction muscle fatigue assessment using time-frequency methods
Description
The use of electromyography (EMG) signals to characterize muscle fatigue has been widely accepted. Initial work on characterizing muscle fatigue during isometric contractions demonstrated that its frequency decreases while its amplitude increases with the onset of fatigue. More recent work concentrated on developing techniques to characterize dynamic contractions for use in clinical and training applications. Studies demonstrated that as fatigue progresses, the EMG signal undergoes a shift in frequency, and different physiological mechanisms on the possible cause of the shift were considered. Time-frequency processing, using the Wigner distribution or spectrogram, is one of the techniques used to estimate the instantaneous mean frequency and instantaneous median frequency of the EMG signal using a variety of techniques. However, these time-frequency methods suffer either from cross-term interference when processing signals with multiple components or time-frequency resolution due to the use of windowing. This study proposes the use of the matching pursuit decomposition (MPD) with a Gaussian dictionary to process EMG signals produced during both isometric and dynamic contractions. In particular, the MPD obtains unique time-frequency features that represent the EMG signal time-frequency dependence without suffering from cross-terms or loss in time-frequency resolution. As the MPD does not depend on an analysis window like the spectrogram, it is more robust in applying the timefrequency features to identify the spectral time-variation of the EGM signal.
Date Created
2012
Contributors
- Austin, Hiroko (Author)
- Papandreou-Suppappola, Antonia (Thesis advisor)
- Kovvali, Narayan (Committee member)
- Muthuswamy, Jitendran (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
ix, 90 p. : ill. (some col.)
Language
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.16046
Statement of Responsibility
by Hiroko Austin
Description Source
Viewed on Oct. 21, 2013
Level of coding
full
Note
Partial requirement for: M.S., Arizona State University, 2012
Note type
thesis
Includes bibliographical references (p. 86-90)
Note type
bibliography
Field of study: Electrical engineering
System Created
- 2013-01-17 06:42:51
System Modified
- 2021-08-30 01:43:20
- 2 years 7 months ago
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