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...

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Main Authors:	Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran
Format:	Conference or Workshop Item
Language:	English
Published:	2012
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/25201/ http://irep.iium.edu.my/25201/ http://irep.iium.edu.my/25201/1/06179000.pdf

id	iium-25201
recordtype	eprints
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 Conference or Workshop Item 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
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Ahsan, Md. Rezwanul Ibrahimy, Muhammad Ibn Khalifa, Othman Omran EMG motion pattern classification through design and optimization of neural network
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%.
format	Conference or Workshop Item
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
title	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_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_sort	emg motion pattern classification through design and optimization of neural network
publishDate	2012
url	http://irep.iium.edu.my/25201/ http://irep.iium.edu.my/25201/ http://irep.iium.edu.my/25201/1/06179000.pdf
first_indexed	2023-09-18T20:37:39Z
last_indexed	2023-09-18T20:37:39Z
_version_	1777409153531117568

EMG motion pattern classification through design and optimization of neural network

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