DocumentCode :
1354578
Title :
Multivariate analysis of muscular fatigue during bicycle ergometer exercise
Author :
Kiryu, Tohru ; Takahashi, Kohsei ; Ogawa, Katsunori
Author_Institution :
Graduate Sch. of Sci. & Technol., Niigata Univ., Japan
Volume :
44
Issue :
8
fYear :
1997
Firstpage :
665
Lastpage :
672
Abstract :
The purpose of this study is to estimate the endurance threshold in terms of muscular fatigue during bicycle ergometer exercise. The problems to be solved are induced by dynamic movement and the physiological variation of muscle activity: that is, the progression and impairment of muscle activity occur simultaneously. First of all, the authors used multichannel recordings of myoelectric (ME) signals to reduce the effect by the movement of a bipolar surface electrode relative to the innervation zones. Second, since even the different types of ME parameters contain redundant information on muscular fatigue, the authors used the principal component analysis (PCA) to represent the meaningful information by small dimensions. Moreover, the authors proposed a total evaluation pattern to discriminate muscular fatigue from progression of muscle force at a glance. The total evaluation pattern shows the proportion of first principal component, the components of the first eigenvector, and the correlation coefficients as a function of the work load. The assessment using the total evaluation pattern divided 8 subjects into 3 groups, whereas these subjects were not identified by a specific ME parameter.
Keywords :
biomechanics; electromyography; medical signal processing; bicycle ergometer exercise; bipolar surface electrode; correlation coefficients; dynamic movement; endurance threshold estimation; first eigenvector; innervation zones; multichannel recordings; multivariate analysis; muscle force; muscular fatigue; myoelectric signals; physiological variation; principal component analysis; total evaluation pattern; work load; Bicycles; Cardiology; Condition monitoring; Electrodes; Fatigue; Frequency; Heart rate; Life estimation; Muscles; Principal component analysis; Adult; Electromyography; Exercise Test; Fatigue; Humans; Male; Multivariate Analysis; Muscle, Skeletal; Reference Values; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.605423
Filename :
605423
Link To Document :
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