Intelligent processing method of electrocardiogram based on deep neural network

Abstract

The invention discloses an intelligent electrocardiogram diagnosis method based on a deep neural network. The intelligent electrocardiogram diagnosis method comprises the steps that 1, signal normalization processing is performed; 2, a training sample space is determined; 3, a verification sample space is determined; 4, a neural network structure is determined; 5, an activation function and an objective function are determined; 6, the neural network is trained; 7, electrocardiogram signals are automatically analyzed. According to the intelligent electrocardiogram diagnosis method based on the deep neural network, data in an MIT-BIH arrhythmia database are taken as samples, the neural network is trained by adopting a Logistic function as the activation function of neurons and adopting a cross entropy cost function as the objective function, an analysis result can be obtained through the trained neural network when the electrocardiogram signals are analyzed, even if a diagnosis doctor does not have very rich clinical experience, a precise diagnosis result can be acquired without needing to consume a large amount of energy of a cardiologist, and therefore the doctor burden is reduced.

Description

technical field [0001] The present invention relates to an intelligent processing method of electrocardiogram based on a deep neural network, and more specifically, to a deep neural network classifier based on large-sample abnormal electrocardiogram data training, which can carry out autonomous learning according to the abnormal types contained in the sample, and construct The intelligent processing method of ECG based on deep neural network can be achieved by using the feature space to achieve the purpose of intelligent processing of ECG. Background technique [0002] The heart is an important organ of the human body. It provides power for the human circulatory system and transports blood to all parts of the body. Its health directly affects various functions of the human body. The electrocardiogram is an intuitive representation of the electrical cycle activity of the heart. Cardiac experts can obtain a lot of information about the heart through the electrocardiogram, so t...

AI Technical Summary

Problems solved by technology

However, the analysis of ECG signals and the construction of feature spaces require the experience and knowledge of heart experts. Engineers not only need to master these profound medical knowledge, but also have to select feature spaces, which consumes a lot of manpower, and the results are often not ideal.

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