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Optimization of neural network for efficient EMG signal classification

Ahsan, Md. Rezwanul and Ibrahimy, Muhammad Ibn and Khalifa, Othman Omran (2012) Optimization of neural network for efficient EMG signal classification. In: 2012 8th International Symposium on Mechatronics and its Applications (ISMA), 10 - 12 April 2012, American University of Sharjah.

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This paper illustrates the classification of Electromyography (EMG) signals through designing and optimization of artificial neural network. The EMG signals obtained for different kinds of hand movements, which are processed to extract the features. Extracted time and timefrequency based feature sets are used to train the neural network. A back-propagation neural network with LevenbergMarquardt training algorithm has been utilized for the classification. The results show that the designed network is optimized for 10 hidden neurons and able to efficiently classify single channel EMG signals with an average rate of 88.4%.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 4637/25207
Uncontrolled Keywords: Electromyography; Neural Network; BackPropagation; Levenberg-Marquardt Algorithm; EMG Signal Classification
Subjects: T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Depositing User: Dr Muhammad Ibrahimy
Date Deposited: 02 Aug 2012 10:19
Last Modified: 18 Sep 2012 14:08
URI: http://irep.iium.edu.my/id/eprint/25207

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