Real-Time Mobile-Based Electrocardiogram System for Remote Monitoring of Patients with Cardiac Arrhythmias

In this study, we propose an electrocardiogram (ECG) system for the simultaneous and remote monitoring of multiple heart patients. It consists of three main components: patient, sever, and monitoring units. The patient unit uses a wearable miniature sensor that continuously measures ECG signals and sends them to a smart mobile phone via a Bluetooth connection. In the mobile device, the ECG signals can be stored, displayed on screen, and automatically transmitted to a distant server unit over the internet; the server stores ECG data from several patients. Health care stakeholders use a monitoring unit to retrieve the ECG signals of multiple patients at any time from the server for display and real-time automatic analysis. The analysis includes segmentation of the ECG signal into separate heartbeats followed by arrhythmia detection and classification. When compared to existing real-time ECG systems, where the detection of abnormalities is usually performed using simple rules, the proposed system implements a real-time classification module that is based on a support vector machine (SVM) classifier. Extensive experimental results on ECG data obtained from a TechPatient TM simulator, a real person, and 20 records from the MIT arrhythmia database are reported and discussed.