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



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Autore: Mokhlesabadifarahani Bita Visualizza persona
Titolo: EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction [[electronic resource] /] / by Bita Mokhlesabadifarahani, Vinit Kumar Gunjan Visualizza cluster
Pubblicazione: Singapore : , : Springer Singapore : , : Imprint : Springer, , 2015
Edizione: 1st ed. 2015.
Descrizione fisica: 1 online resource (43 p.)
Disciplina: 502.85
570285
610.28
614.1
616.7
617.03
620
621.3848
Soggetto topico: Biomedical engineering
Orthopedics
Forensic science
Bioinformatics
Health informatics
Rehabilitation
Biomedical Engineering and Bioengineering
Forensic Science
Computational Biology/Bioinformatics
Health Informatics
Persona (resp. second.): GunjanVinit Kumar
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: Introduction to EMG Technique and Feature Extraction -- Methodology for  working with EMG dataset -- Results -- Conclusions and Inferences of Present Study.
Sommario/riassunto: 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.
Titolo autorizzato: EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction  Visualizza cluster
ISBN: 981-287-320-1
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910299687003321
Lo trovi qui: Univ. Federico II
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Serie: SpringerBriefs in Forensic and Medical Bioinformatics, . 2196-8845