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- Author: Bita Mokhlesabadifarahani
- Publisher: Springer
- Year: 2015
- Pages: 35
- ISBN-10: 9812873198
- ISBN-13: 9789812873194
- Format: 15.6 x 23.4 x 0.3 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
Emg Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction (e-book) (used book) | bookbook.eu
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Description
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.
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- Author: Bita Mokhlesabadifarahani
- Publisher: Springer
- Year: 2015
- Pages: 35
- ISBN-10: 9812873198
- ISBN-13: 9789812873194
- Format: 15.6 x 23.4 x 0.3 cm, softcover
- Language: English English
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.
Reviews