EMG Signals Characterization in Three States of Contraction by Fuzzy Network and Feature Extraction
| By: | Bita Mokhlesabadifarahani; Vinit Kumar Gunjan |
| Publisher: | Springer Nature |
| Print ISBN: | 9789812873194 |
| eText ISBN: | 9789812873200 |
| Edition: | 0 |
| Copyright: | 2015 |
| Format: | Reflowable |
eBook Features
Instant Access
Purchase and read your book immediately
Read Offline
Access your eTextbook anytime and anywhere
Study Tools
Built-in study tools like highlights and more
Read Aloud
Listen and follow along as Bookshelf reads to you
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.