the aide diagnosis of cardiac heart diseases using a...

The Aide Diagnosis of Cardiac Heart Diseases Usinga Deoxyribonucleic Acid Based Backpropagation

Neural Network

LI SHI, ZHIZHONG WANG, LIJIA WANG,and JINYING ZHANG

School of Electric Engineering, Zhengzhou University, China

In this paper, a novel diagnostic scheme of cardiac heart diseases is presented using aDeoxyribonucleic Acid (DNA)-based BP(DNA-BP) Neural Network by distinguishing the shapes ofST segments automatically. First, wavelet transform is applied to extract the ST segments byidentifying the characteristic points in the ECG. ECG signals are decomposed by aTrous Algorithmusing dyadic spline wavelets. The relationship between the feature points of ECG signals and themodulus maximum pairs of the signals’ wavelet transform is established, and the R-wave and STsegment’s fiducial points are extracted at different wavelet scales. Second, in order to overcome thedisadvantages of the BP neural network, a DNA optimization method is adopted to optimize theoriginal weights and bias of a BP neural network. The BP algorithm is used to find the most optimalvalues of the weights and bias of the BP network. At last the effectiveness of the proposed aideddiagnostic scheme is demonstrated via the experiments which the data are from the clinical study andMIT/BIH ECG data base. In order to validate the advantages of the DNA-based BP (DNA-BP)network and determine the best application conditions of the network, two types of experiments wereconducted. In each experiment, 30 samples were selected as the training data and testing datarespectively. In the first type of experiments, the data were obtained from the ECG of differentpeople. While in the second type of experiments, the data were obtained from the ECG of one personat different times. The same data and the conditions were used in both BP and GA-based BP (GA-BP)networks to illustrate the advantages of the proposed DNA-based BP network. The experiment resultsillustrate that the proposed DNA-based BP network overcomes the limitation of the sloping method inidentifying straight line ST segments and the limitation of function fitting method in fitting accuracy. Italso surmounts the disadvantages of a BP network in terms of the local minimum, slow convergence,and the shortcomings of GA-BP in terms of its limitation in algorithm coding and evolution ways.

In conclusion, the neural network is used to supply an invaluable aid for physicians to diagnosecardiac heart diseases and myocardial infarction.

International Journal of Distributed Sensor Networks, 5: 38, 2009

Copyright � Taylor & Francis Group, LLC

ISSN: 1550-1329 print / 1550-1477 online

DOI: 10.1080/15501320802533418

Address correspondence to Li Shi, School of Electric Engineering, Zhengzhou University,450001, China. E-mail: [email protected]

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