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EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction - 2015 ed.

By: (Author) Bita Mokhlesabadifarahani , (Author) Vinit Kumar Gunjan

Extended Catalogue

Ksh 8,100.00

Format: Paperback or Softback

ISBN-10: 9812873198

ISBN-13: 9789812873194

Edition: 2015 ed.

Series: SpringerBriefs in Forensic and Medical Bioinformatics

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 (height x width x thickness): 15.80 x 23.70 x 0.50 cms

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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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