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

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

By Bita Mokhlesabadifarahani & Vinit Kumar Gunjan Engineering 10/02/2015

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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EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction Bita Mokhlesabadifarahani & Vinit Kumar Gunjan
EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction
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