EMG motion pattern classification through design and optimization of neural network
This paper illustrates the classification of EMG signals through design and optimization of Artificial Neural Network (ANN). Different types of ANN models are basically structured with many interconnected network elements which can develop pattern classification strategies based on a set of input/tr...
| Main Authors: | , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2012
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/25201/ http://irep.iium.edu.my/25201/1/06179000.pdf |
| _version_ | 1848779426531115008 |
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| author | Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran |
| author_facet | Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran |
| author_sort | Ahsan, Md. Rezwanul |
| building | IIUM Repository |
| collection | Online Access |
| description | This paper illustrates the classification of EMG signals through design and optimization of Artificial Neural Network (ANN). Different types of ANN models are basically structured with many interconnected network elements which can develop pattern classification strategies based on a set of input/training data. The ANN models work in parallel thus providing higher computational performance than traditional classifiers which function sequentially. The EMG signals obtained for different kinds of hand motions, which further denoised and processed to extract the features. Extracted time and time-frequency based feature sets are used to train the neural network. A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. The results show that the designed network is optimized for 10 hidden neurons with 7 input features and able to efficiently classify single channel EMG signals with an average success rate of 88.4%.
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| first_indexed | 2025-11-14T15:17:35Z |
| format | Proceeding Paper |
| id | iium-25201 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:17:35Z |
| publishDate | 2012 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-252012012-08-30T08:08:29Z http://irep.iium.edu.my/25201/ EMG motion pattern classification through design and optimization of neural network Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran T Technology (General) This paper illustrates the classification of EMG signals through design and optimization of Artificial Neural Network (ANN). Different types of ANN models are basically structured with many interconnected network elements which can develop pattern classification strategies based on a set of input/training data. The ANN models work in parallel thus providing higher computational performance than traditional classifiers which function sequentially. The EMG signals obtained for different kinds of hand motions, which further denoised and processed to extract the features. Extracted time and time-frequency based feature sets are used to train the neural network. A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. The results show that the designed network is optimized for 10 hidden neurons with 7 input features and able to efficiently classify single channel EMG signals with an average success rate of 88.4%. 2012-04-05 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/25201/1/06179000.pdf Ahsan, Md. Rezwanul and Ibrahimy, Muhammad Ibn and Khalifa, Othman Omran (2012) EMG motion pattern classification through design and optimization of neural network. In: 2012 International Conference on Biomedical Engineering (ICoBE), 27-28 February, 2012, Penang, Malaysia. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=6179000&contentType=Conference+Publications |
| spellingShingle | T Technology (General) Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran EMG motion pattern classification through design and optimization of neural network |
| title | EMG motion pattern classification through design and optimization of neural network |
| title_full | EMG motion pattern classification through design and optimization of neural network |
| title_fullStr | EMG motion pattern classification through design and optimization of neural network |
| title_full_unstemmed | EMG motion pattern classification through design and optimization of neural network |
| title_short | EMG motion pattern classification through design and optimization of neural network |
| title_sort | emg motion pattern classification through design and optimization of neural network |
| topic | T Technology (General) |
| url | http://irep.iium.edu.my/25201/ http://irep.iium.edu.my/25201/ http://irep.iium.edu.my/25201/1/06179000.pdf |