Heart Disease Classification Using One Dimensional Convolutional Neural Network

Abstract: In a body sensor network, vital signs such as heart rate, temperature and activity can be continuously tracked by wearable computers and relayed by personal devices to the cloud infrastructure, for both real-time health management and long-term health statistics purposes. However, along with boosting smart health sensors and applications, there are also increasing Heart Disease Detection requirements, which indicates that the given ECG of a particular person is normal or abnormal (abnormality is like heart attack and arrhythmia(An arrhythmia is a problem with the rate or rhythm of your heartbeat.). Heart Disease Classification is a promising technology for automatic and accurate individual recognition, focusing on these challenges.

Keywords: ECG, wavelet transformation, convolutional neural network, blind signal processing, data representation.