Research On Early Detection Of Myocardial Ischemia Via Cardiodynamicsgram And Echo State Network

Electrocardiogram(ECG)is the most commonly used method for early detection of myocardial ischemia,because ECG detection is inexpensive,easy to operate,and has no trauma to the body.However,the diagnostic accuracy of myocardial ischemia based on ECG is much lower than that of other traumatic methods.Therefore,many scholars have spent much time on ECG researching,but most of these studies only consider ECG as a kind of static mode.Deterministic learning theory is a new theory in the field of intelligent control,which can realize knowledge-learning,knowledge-expression,knowledge-storage and knowledge-reuse in an unknown dynamic environment.The early detection of myocardial ischemia via deterministic learning theory regards ECG as a dynamic model,extracting the dynamic characteristics of ST-T segment,and projecting it into three-dimensional space(Cardiodynamicsgram,CDG),according to the shape of CDG,satisfactory accuracy can be obtained.Classification of CDG based on its shape is only a qualitative analysis.In order to classify CDG more scientifically and effectively,this paper uses an ensemble model composed of multiple functional echo state networks as classifier.The echo state network is a special kind of recurrent neural network,it replaces the hidden layer with the “reservoir”.It only needs to train the connection weight between the “reservoir” and the output layer,which makes the training process very simple.The functional echo state network is a special kind of echo state network,which retains the advantage of fast training,and also solves the problem that the echo state network cannot directly classify the time series.For the same task to be classified,this paper uses a certain number of functional echo state networks to generate an ensemble classifier,which can reduce the impact of random parameters brought by single functional echo state network.The experimental results show that the ensemble classifier performs well in CDG classification.In order to popularize the algorithm proposed in this paper into the actual medical environment,a WPF-based myocardial ischemia detection system is developed,through C# and C++ mixed programming,the Armadillo linear algebra library can be used to solve matrix operation problems in the proposed algorithm.The main functions of the system include data acquisition,data preprocessing and diagnostic analysis.The implementation of the system laid a solid foundation for further testing of the algorithm.