Significant difference analysis of myocardial ischemia indicators based on synthesized algorithm

Abstract

Electrocardiogram (ECG) is a record of the electrical activity of the heart, which is widely used in medical treatment. In this paper, a synthesized algorithm is proposed with methods of multiresolution wavelet decomposition and reconstruction, self-adaptive threshold, maximum and minimum modulus and area integration techniques to extract the feature points of ECG. The synthesized algorithm achieves higher accuracy and precision in the data validation based on QT Database of PhysioNet. Besides, ST segment length and RT interval are introduced as indicators of myocardial ischemia. The synthesized algorithm is adopted to extract these two indicators in Long-term ST Database of PhysioNet. The correlation between myocardial ischemia and the two indicators is verified by their significant difference analysis of before, during and after myocardial ischemic episode.