Publication: Application of Wavelet Transform to identify motor unit recruitment pattern
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Issued Date
2010
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-79955387606
Rights Holder(s)
มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
Proceedings of 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2010. Vol , No. (2010), p.242-245
Suggested Citation
Paobthong N., Boonsinsukh R., Saengsirisuwan V., Sirisup S. Application of Wavelet Transform to identify motor unit recruitment pattern. Proceedings of 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2010. Vol , No. (2010), p.242-245. doi:10.1109/IECBES.2010.5742236 Retrieved from: https://hdl.handle.net/20.500.14740/7465
Abstract
Motor unit recruitment pattern represents the time-frequency characteristics of muscle contraction. The Continuous Wavelet Transform (CWT) is a time-frequency signal analysis but its ability to identify motor unit recruitment pattern is still unclear. The purpose of this study was to validate the CWT in identifying the differences in motor unit recruitment pattern, regarding time-space domains, between young and elderly healthy subjects during maximum voluntary knee extension. Ten elderly and 10 young subjects participated in this study. They were asked to perform isometric knee extension at 100% maximum voluntary contraction for 10 seconds. CWT analysis was presented as scalogram. Results showed that the presence of red color spectrum in the young subjects was less than that in the elderly group, indicating that the major recruitments occur more frequently in the elderly. When considering the neuronal firing frequency, the elderly subject operates the firing frequency at a lower range than the young group. The findings in this study confirmed that the CWT can be used to identify the age-related changes in motor unit recruitment pattern. © 2010 IEEE.
Subject(s)
Age-related changes
Aging
Color spectra
Continuous wavelet transforms
Firing frequency
Healthy subjects
Knee extension
Maximum voluntary contraction
Motor unit
Motor unit recruitment pattern
Muscle contractions
Neuronal firings
Time-frequency characteristics
Time-frequency signal analysis
Time-space
Wavelet
Biomedical engineering
Employment
Muscle
Wavelet transforms
Aging
Color spectra
Continuous wavelet transforms
Firing frequency
Healthy subjects
Knee extension
Maximum voluntary contraction
Motor unit
Motor unit recruitment pattern
Muscle contractions
Neuronal firings
Time-frequency characteristics
Time-frequency signal analysis
Time-space
Wavelet
Biomedical engineering
Employment
Muscle
Wavelet transforms