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

Authors: Bita Mokhlesabadifarahani, Vinit Kumar Gunjan

Publisher: Springer Singapore

Book Series : SpringerBriefs in Applied Sciences and Technology

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

About this book

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.

Backmatter

Title: EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction
Authors: Bita Mokhlesabadifarahani
Vinit Kumar Gunjan
Publisher: Springer Singapore
Electronic ISBN: 978-981-287-320-0
Print ISBN: 978-981-287-319-4
DOI: https://doi.org/10.1007/978-981-287-320-0

Springer Professional

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

About this book

Table of Contents

Frontmatter

Chapter 1. Introduction to EMG Technique and Feature Extraction

Chapter 2. Methodology for Working with EMG Dataset

Chapter 3. Results

Chapter 4. Conclusions and Inferences of Present Study

Backmatter