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Methods Inf Med 1997; 36(04/05): 302-305
DOI: 10.1055/s-0038-1636867
Original Article
Schattauer GmbH

Multivariate Analysis of Multichannel Surface Myoelectric Signals to Determine Muscular Fatigue

Y. Nakamura
1   Graduate School of Science and Technology, Niigata University, Niigata, Japan
1   Graduate School of Science and Technology, Niigata University, Niigata, Japan
,
T. Kiryu
1   Graduate School of Science and Technology, Niigata University, Niigata, Japan
1   Graduate School of Science and Technology, Niigata University, Niigata, Japan
,
Y. Saitoh
1   Graduate School of Science and Technology, Niigata University, Niigata, Japan
1   Graduate School of Science and Technology, Niigata University, Niigata, Japan
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Publikationsdatum:
19. Februar 2018 (online)

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Abstract:

Multivariate analysis would be effective in finding the functional change from several variables obtained from multivariate biological signals. We applied this idea to the discrimination of sustained fatiguing contraction from negative ramp contraction. The time-series of eigenvalues were obtained from multidimensional biological variables by the Karhunen-Loève expansion. The results showed that, the first and second eigenvalues came close to each other during fatiguing contraction, whereas only the first eigenvalue was dominant during negative ramp contraction. Moreover, the factor loadings showed considerable difference between fatiguing contraction and negative ramp contraction. As a result, the muscular-fatigue-related functional change could be represented clearly by the time-series of proportions and factor loadings.

Keywords:

Muscular Fatigue - Karhunen-Loève Expansion - Eigenvalue - Factor Loading
 

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