A deep learning framework for heart disease classification in an IoTs-based system

Abstract

Accurate classification of heart diseases plays an important role and IoTs applied in a medical system will increase the effectiveness of diagnosis. In this chapter, we propose an IoTs-based diagnostic system for heart diseases classification. This system is designed to transmit classified data to server for storage and diagnosis. In particular, ECG devices are connected to internet systems through wifi or 3G/4G technologies for transmitting ECG data to a cloud-based processing system for storing patient’s profiles. Therefore, datasets are pre-processed for extracting features using a WPD algorithm. In addition, a wkPCA method and a deep learning framework are employed for classifying heart diseases. Experimental results and the IoTs-based system description are shown to illustrate the effectiveness of the proposed method.