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