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

By: Mokhlesabadifarahani, Bita., autor.
Contributor(s): Gunjan, Vinit Kumar., autor.
Material type: materialTypeLabelE-bookSeries: (SpringerBriefs in Forensic and Medical Bioinformatics,, 2196-8845); (Engineering (Springer-11647)).Publisher: Singapore : Springer International Publishing, 2015Description: 1 recurso en línea (XV, 35 páginas 17 ilustraciones, 13 ilustraciones a color.).ISBN: 9789812873200.Subject: Procesadores digitales de señalOnline resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Introduction to EMG Technique and Feature Extraction -- Methodology for  working with EMG dataset -- Results -- Conclusions and Inferences of Present Study.
Abstract: 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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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería TK5102.9 M654 2015 EB (Browse shelf(Opens below)) Acceso electrónico eBook.12112215
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Introduction to EMG Technique and Feature Extraction -- Methodology for  working with EMG dataset -- Results -- Conclusions and Inferences of Present Study.

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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