Volume 3, Issue 1, May 2013, Pages 145–150
D. Prakash1, T. Uma Mageshwari2, K. Prabakaran3, and A. Suguna4
1 Electrical and Electronics Engineering, Anna University Regional Centre Coimbatore, Coimbatore - 641 047, Tamilnadu, India
2 Electrical and Electronics Engineering, Anna University Regional Centre Coimbatore, Coimbatore - 641 047, Tamilnadu, India
3 Assistant Professor, Electronics and Instrumentation Engineering, Erode Sengunthar Engineering College, Thudupathi, Erode, Tamilnadu, 638057, India
4 Electrical and Electronics Engineering, Anna University Regional Centre Coimbatore, Coimbatore - 641 047, Tamilnadu, India
Original language: English
Copyright © 2013 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
An artificial intelligence (AI) algorithm has been developed using Mathematical formula to diagnose heart disease from Phonocardiogram (PCG) signals. Auscultation, the technique of listening to heart sounds with a stethoscope can be used as a primary detection technique for detecting heart disorders for the past years. But now the Phonocardiogram, the digital recording of heart sounds is becoming very popular technique as it is relatively inexpensive. Four amplitude parameters of the PCG signal are extracted by using filter technique and are used as input. PCG signals for three types of heart diseases such as Tachycardia, Bradycardia and Atrial fibrillation were used in this paper to test the accuracy. These disease types that affect the electrical system of heart are known as arrhythmias, cause the heart to beat very fast (Tachycardia) or very slow (Bradycardia), or unexpectedly (Atrial fibrillation). After the signals are filtered and the parameters are extracted, the parameters are fed to the AI algorithm. Classifications of heart diseases are carried using the AI algorithm by comparing the extracted parameters. Here comparison is done using Min Max method. The developed mathematical artificial intelligence algorithm is implemented in MATLab using Simulink and the simulation results proved that the developed algorithm has been shown to be a powerful technique in detection of heart diseases using PCG signals.
Author Keywords: Artificial intelligence, Atrial fibrillation, Bradycardia, Heart, MATLab, Phonocardiogram signals, Tachycardia.
D. Prakash1, T. Uma Mageshwari2, K. Prabakaran3, and A. Suguna4
1 Electrical and Electronics Engineering, Anna University Regional Centre Coimbatore, Coimbatore - 641 047, Tamilnadu, India
2 Electrical and Electronics Engineering, Anna University Regional Centre Coimbatore, Coimbatore - 641 047, Tamilnadu, India
3 Assistant Professor, Electronics and Instrumentation Engineering, Erode Sengunthar Engineering College, Thudupathi, Erode, Tamilnadu, 638057, India
4 Electrical and Electronics Engineering, Anna University Regional Centre Coimbatore, Coimbatore - 641 047, Tamilnadu, India
Original language: English
Copyright © 2013 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
An artificial intelligence (AI) algorithm has been developed using Mathematical formula to diagnose heart disease from Phonocardiogram (PCG) signals. Auscultation, the technique of listening to heart sounds with a stethoscope can be used as a primary detection technique for detecting heart disorders for the past years. But now the Phonocardiogram, the digital recording of heart sounds is becoming very popular technique as it is relatively inexpensive. Four amplitude parameters of the PCG signal are extracted by using filter technique and are used as input. PCG signals for three types of heart diseases such as Tachycardia, Bradycardia and Atrial fibrillation were used in this paper to test the accuracy. These disease types that affect the electrical system of heart are known as arrhythmias, cause the heart to beat very fast (Tachycardia) or very slow (Bradycardia), or unexpectedly (Atrial fibrillation). After the signals are filtered and the parameters are extracted, the parameters are fed to the AI algorithm. Classifications of heart diseases are carried using the AI algorithm by comparing the extracted parameters. Here comparison is done using Min Max method. The developed mathematical artificial intelligence algorithm is implemented in MATLab using Simulink and the simulation results proved that the developed algorithm has been shown to be a powerful technique in detection of heart diseases using PCG signals.
Author Keywords: Artificial intelligence, Atrial fibrillation, Bradycardia, Heart, MATLab, Phonocardiogram signals, Tachycardia.
How to Cite this Article
D. Prakash, T. Uma Mageshwari, K. Prabakaran, and A. Suguna, “Detection of Heart Diseases by Mathematical Artificial Intelligence Algorithm Using Phonocardiogram Signals,” International Journal of Innovation and Applied Studies, vol. 3, no. 1, pp. 145–150, May 2013.
