Description

Book Synopsis
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.

Table of Contents
Introduction to EMG Technique and Feature Extraction.- Methodology for working with EMG dataset.- Results.- Conclusions and Inferences of Present Study.

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

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    A Paperback by Bita Mokhlesabadifarahani, Vinit Kumar Gunjan

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      View other formats and editions of EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction by Bita Mokhlesabadifarahani

      Publisher: Springer Verlag, Singapore
      Publication Date: 11/03/2015
      ISBN13: 9789812873194, 978-9812873194
      ISBN10: 9812873198
      Also in:
      Biomedical engineering / Medical engineering Surgical orthopaedics and fractures Forensic science

      Description

      Book Synopsis
      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.

      Table of Contents
      Introduction to EMG Technique and Feature Extraction.- Methodology for working with EMG dataset.- Results.- Conclusions and Inferences of Present Study.

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