The Implementation Of The Early Myocardial Ischemia Aided Diagnosis Batch Mode Learning System

With the development of economy and society, people’s living habits are constantly changing, and the harmfulness of human cardiovascular disease is greatly improved. Among them, especially the myocardial ischemia and myocardial infarction, their range of the influence has spread all over the world, and affecting all ages. Myocardial ischemia and myocardial infarction are becoming the number one killer disease in human society, which worthy of our attention.Deterministic learning theory is based on the radial basis function neural network, which can achieve locally accurate modeling of the continuous nonlinear dynamic system with periodic or return trajectory. Early myocardial ischemia aided diagnosis system in this paper uses deterministic learning theory and the method of dynamic pattern recognition, to achieve the training, learning and recognition of the subject’s ECG data with the help of neural network. This method, through the measurement in the traditional ECG way, analyze and process the ECG data, which has the characteristics of simple, quick, noninvasive, economy.Focusing on the constantly increasing ECG data, this paper designs the batch mode learning system, describes in detail the architecture, and verifies the auxiliary diagnosis results of the batch mode learning. The use of the batch mode learning system, saves plenty of time, provides a great convenience to the users. Considering the consistency of the whole system, we use Matlab GUI to design the entire early myocardial ischemia aided diagnosis system, including the ECG data acquisition system, single mode learning system, batch mode learning system and pattern database, recognition and so. The system uses Jacket Engine to finish the organic combination with Matlab. Through the SQL Server 2008, the system completes the management of the pattern database, and provides support for pattern recognition. The early myocardial ischemia aided diagnosis system can provide early aided diagnosis and rapid identification of myocardial ischemia to the doctors, and create a good condition to solve this kind of clinical problem.