EMG signals characterization in three states of contraction by fuzzy network and feature extraction: [electronic resource] /: Bita Mokhlesabadifarahani, Vinit Kumar Gunjan.

Mokhlesabadifarahani, Bita,; Gunjan, Vinit Kumar,

doi:10.1007/978-981-287-320-0

EMG signals characterization in three states of contraction by fuzzy network and feature extraction [electronic resource] / Bita Mokhlesabadifarahani, Vinit Kumar Gunjan.

Mokhlesabadifarahani, Bita, author.; Gunjan, Vinit Kumar, author.

2015

TK5102.9

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Title

EMG signals characterization in three states of contraction by fuzzy network and feature extraction [electronic resource] / Bita Mokhlesabadifarahani, Vinit Kumar Gunjan.

Author

Mokhlesabadifarahani, Bita, author.

ISBN

9789812873200 electronic book
9812873201 electronic book
9789812873194

DOI

https://doi.org/10.1007/978-981-287-320-0

Published

Singapore : Springer, [2015]

Copyright

Language

English

Description

1 online resource (xv, 35 pages) : illustrations (some color).

Item Number

10.1007/978-981-287-320-0 doi

Call Number

TK5102.9

Dewey Decimal Classification

621.382/2

Summary

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.

Bibliography, etc. Note

Includes bibliographical references.

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Access limited to authorized users.

Source of Description

Online resource; title from PDF title page (SpringerLink, viewed February 18, 2015).

Added Author

Gunjan, Vinit Kumar, author.

Series

SpringerBriefs in applied sciences and technology. Forensic and medical bioinformatics.

Available in Other Form

Print version: 9789812873194