A CARDIOLOGY APPLICATION USING AN ARTIFICIAL NEURAL NETWORK MODEL
Shokr, M., Shaarawy, M., Abo Elsoud, H. (1999). A CARDIOLOGY APPLICATION USING AN ARTIFICIAL NEURAL NETWORK MODEL. EKB Journal Management System, 2(2nd International Conference on Electrical Engineering ICEENG 1999), 312-326. doi: 10.21608/iceeng.1999.62515
M. Shokr; M. Shaarawy; H. Abo Elsoud. "A CARDIOLOGY APPLICATION USING AN ARTIFICIAL NEURAL NETWORK MODEL". EKB Journal Management System, 2, 2nd International Conference on Electrical Engineering ICEENG 1999, 1999, 312-326. doi: 10.21608/iceeng.1999.62515
Shokr, M., Shaarawy, M., Abo Elsoud, H. (1999). 'A CARDIOLOGY APPLICATION USING AN ARTIFICIAL NEURAL NETWORK MODEL', EKB Journal Management System, 2(2nd International Conference on Electrical Engineering ICEENG 1999), pp. 312-326. doi: 10.21608/iceeng.1999.62515
Shokr, M., Shaarawy, M., Abo Elsoud, H. A CARDIOLOGY APPLICATION USING AN ARTIFICIAL NEURAL NETWORK MODEL. EKB Journal Management System, 1999; 2(2nd International Conference on Electrical Engineering ICEENG 1999): 312-326. doi: 10.21608/iceeng.1999.62515

A CARDIOLOGY APPLICATION USING AN ARTIFICIAL NEURAL NETWORK MODEL

The International Conference on Electrical Engineering
Article 33, Volume 2, 2nd International Conference on Electrical Engineering ICEENG 1999, November 1999, Page 312-326  XML PDF (3.52 MB)
Document Type: Original Article
DOI: 10.21608/iceeng.1999.62515
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Authors
M. Shokr1, 2; M. Shaarawy3, 2; H. Abo Elsoud4
1Dr., Dept. of Computer & Operation Research, Military Technical Collage.+
2Egyptian Armed Forces.
3Ass. Prof. Dr., Dept. of Computer & Operation Research, Military Technical Collage.+
4Eng., Egyptian Armed Forces.
Abstract
In this paper, a Neural Network Model is designed for the classification of normal and abnormal electrocardiography (ECG) signals. Linear Prediction Coding (LPC) is used for extracting the features of the signals generated from each patient. The features of the signals are applied as inputs to train and test the Neural Network. Different Neural Network architectures investigated in order to achieve a better performance. Test results show that, the classification accuracy of the network can reach 98 %.
Keywords
Artificial Neural Networks (ANN); Electrocardiograph (ECG); Back Propagation Network (BPN); Linear Prediction Coding (LPC)
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