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

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Mokhlesabadifarahani, Bita (Autor), Gunjan, Vinit Kumar (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Singapore : Springer Nature Singapore : Imprint: Springer, 2015.
Edición:1st ed. 2015.
Colección:SpringerBriefs in Forensic and Medical Bioinformatics,
Temas:
Acceso en línea:Texto Completo
Descripción
Sumario: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.
Descripción Física:XV, 35 p. 17 illus., 13 illus. in color. online resource.
ISBN:9789812873200
ISSN:2196-8853