EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction

2015 ed.

by Bita Mokhlesabadifarahani , Vinit Kumar Gunjan

Book Details

Format Paperback / Softback

Book Series SpringerBriefs in Forensic and Medical Bioinformatics

ISBN-10 9812873198

ISBN-13 9789812873194

Edition 2015 ed.

Publisher Springer Verlag, Singapore

Imprint Springer Verlag, Singapore

Country of Manufacture SG

Country of Publication GB

Publication Date Mar 11th, 2015

Print length 35 Pages

Weight 102 grams

Dimensions 15.80 x 23.70 x 0.50 cms

Product Classification: Musculoskeletal medicine Biomedical engineering

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Different structures of the neuro-fuzzy classifier are also comparatively analyzed to find the optimum structure of the classifier used.

Neuro-muscular and musculoskeletal disorders and injuries highly affect the life style and the motion abilities of an individual. This brief highlights a systematic method for detection of the level of muscle power declining in musculoskeletal and Neuro-muscular disorders. The neuro-fuzzy system is trained with 70 percent of the recorded Electromyography (EMG) cut off window and then used for classification and modeling purposes. The neuro-fuzzy classifier is validated in comparison to some other well-known classifiers in classification of the recorded EMG signals with the three states of contractions corresponding to the extracted features. Different structures of the neuro-fuzzy classifier are also comparatively analyzed to find the optimum structure of the classifier used.

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