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EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction [Repost]
![EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction [Repost]](https://pixhost.icu/avaxhome/2c/0e/00430e2c.jpg)
Bita Mokhlesabadifarahani, Vinit Kumar Gunjan - EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction
Published: 2015-02-12 | ISBN: 9812873198 | PDF | 35 pages | 2.86 MB
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.