A METHOD TO DETECT MYOCARDIAL ISCHEMIA USING COMPARISON ANALYSIS OF HEART RATE VARIABILITY TIME AND FREQUENCY DOMAIN FEATURES

摘要

PURPOSE: A method for detecting myocardial ischemia is provided to improve the overall sensing accuracy of myocardial ischemia. CONSTITUTION: A weighting fuzzy membership function based neural network is learned using data set for the neural learning(S100). A grouping model of a time domain and a grouping model of a frequency domain are constructed based on the learned weighting fuzzy membership function based neural network(S200). The myocardial ischemia data of a patient is detected by applying patient's date to the constructed grouping model of a time domain and a grouping model of a frequency domain(S300). [Reference numerals] (S100) Learning a weighting fuzzy membership function based neural network; (S200) Constructing the grouping model of a time domain and the grouping model of a frequency domain; (S300) Detecting the myocardial ischemia data of a patient