DocumentCode
1082448
Title
Single motor unit myoelectric signal analysis with nonstationary data
Author
Englehart, Kevin B. ; Parker, Philip A.
Author_Institution
Inst. of Biomed. Eng., New Brunswick Univ., Fredericton, NB, Canada
Volume
41
Issue
2
fYear
1994
Firstpage
168
Lastpage
180
Abstract
The information content of the myoelectric signal (MES) is commonly revealed by statistical measures in the time or frequency domain. Empirical analyses of the MES from a single motor unit have generally assumed that features are invariant with time. Theoretical and experimental work has been done to demonstrate how nonstationary behavior in the discharge statistics of a motor neuron may affect estimates of features extracted from the motor unit´s contribution to the MES. Specifically, it has been shown that nonstationary behavior can markedly influence estimates of features describing motor neuron firing behavior and consequently, the low-frequency portion of the MES power spectral density. These results may help to explain the discrepancies in the literature which report empirical models of motor neuron firing statistics.
Keywords
bioelectric potentials; medical signal processing; muscle; physiological models; statistical analysis; empirical models; frequency domain; literature discrepancies; motor neuron discharge statistics; motor neuron firing statistics; myoelectric signal information content; nonstationary data; power spectral density; single motor unit myoelectric signal analysis; statistical measures; time domain; Biomedical engineering; Biomedical measurements; Data analysis; Frequency; Muscles; Neurons; Recruitment; Shape measurement; Signal analysis; Statistics; Algorithms; Electrophysiology; Linear Models; Models, Biological; Motor Neurons; Muscle Contraction; Probability; Synaptic Transmission;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/10.284928
Filename
284928
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