A New Method and System Designed for CAD Noninvasive Detecting

A new method for noninvasive detecting coronary artery disease(CAD) based on BP artificial neural network (ANN) is presented, and the diagnosis system is designed. The ECG signals from body surface are proceeded, and four character parameters (RR interval, width of QRS complex, scope and slope of ST segment) of the ECG, correlating with CAD, are computed. CAD is detected and diagnosed by using BPANN, which is imputed with character parameters of the ECG, blood pressure and basic information (sex, age, weight, smoking or not). Experiment results show that the method mentioned in this paper may be applied and easily manipulated for CAD diagnosis.