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
Link To Document :
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