Investigation on parametric analysis of dynamic EMG signals by a muscle-structured simulation model

For the analysis of electromyographic (EMG) signals during dynamic movement, the authors propose an estimation algorithm for the time-varying parameters of an autoregressive model. The parameters correspond to less biased time-varying reflection coefficients. The authors determined the less biased e...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 1992-03, Vol.39 (3), p.280-288
Main Authors: Kiryu, T., Saitoh, Y., Ishioka, K.
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Algorithms
Analog-Digital Conversion
Analytical models
Biological and medical sciences
Electrodiagnosis. Electric activity recording
Electromyography
Fatigue
Humans
Investigative techniques, diagnostic techniques (general aspects)
Least-Squares Analysis
Life estimation
Masseter Muscle - physiology
Medical sciences
Models, Biological
Muscle Contraction - physiology
Muscles
Nervous system
Parameter estimation
Recruitment
Reference Values
Reflection
Signal analysis
Signal Processing, Computer-Assisted
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Summary:For the analysis of electromyographic (EMG) signals during dynamic movement, the authors propose an estimation algorithm for the time-varying parameters of an autoregressive model. The parameters correspond to less biased time-varying reflection coefficients. The authors determined the less biased estimation using a locally quasi-stationary model and named these parameters 'k parameters.' They estimated k parameters up to the fifth order for the surface EMG signals of a masseter muscle during rapid open-close movement of the lower jaw, a ballistic contraction, and fatigue. According to the results, the time courses of the k parameters displayed remarkable properties. In order to study the behavior of k parameters physiologically, the authors produced a muscle-structured simulation model based on anatomical and physiological data. The simulation results suggested that the behavior of the third parameter is related to the number of active motor units (MUs) at the shallow layer of a muscle. The detailed recruitment mechanism in terms of the MU types has not yet been solved.< >
ISSN:0018-9294
1558-2531
DOI:10.1109/10.125013