Emg Signals Characterization In Three States Of Contraction By Fuzzy Network And Feature Extraction


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


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

Author: Bita Mokhlesabadifarahani

language: en

Publisher: Springer

Release Date: 2015-02-10


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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.

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


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

Author: Bita Mokhlesabadifarahani

language: en

Publisher:

Release Date: 2015


DOWNLOAD





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.

Proceedings of the 4th International Conference on Data Science, Machine Learning and Applications


Proceedings of the 4th International Conference on Data Science, Machine Learning and Applications

Author: Amit Kumar

language: en

Publisher: Springer Nature

Release Date: 2023-08-15


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This book includes peer reviewed articles from the 4th International Conference on Data Science, Machine Learning and Applications, 2022, held at the Hyderabad Institute of Technology & Management on 26-27th December, India. ICDSMLA is one of the most prestigious conferences conceptualized in the field of Data Science & Machine Learning offering in-depth information on the latest developments in Artificial Intelligence, Machine Learning, Soft Computing, Human Computer Interaction, and various data science & machine learning applications. It provides a platform for academicians, scientists, researchers and professionals around the world to showcase broad range of perspectives, practices, and technical expertise in these fields. It offers participants the opportunity to stay informed about the latest developments in data science and machine learning.