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Emg Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction (Springerbriefs in Applied Sciences and Technology)
Bita Mokhlesabadifarahani; Vinit Kumar Gunjan (Autor)
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Springer
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Emg Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction (Springerbriefs in Applied Sciences and Technology) - Bita Mokhlesabadifarahani; Vinit Kumar Gunjan
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Reseña del libro "Emg Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction (Springerbriefs in Applied Sciences and Technology)"
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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