Remote health monitoring system for detecting cardiac disorders

• Published in: IET systems biology 2015-12, Vol.9 (6), p.309-314
• Main Authors: Bansal, Ayush, Kumar, Sunil, Bajpai, Anurag, Tiwari, Vijay N, Nayak, Mithun, Venkatesan, Shankar, Narayanan, Rangavittal
• Format: Article
• Language: English
• Subjects: Algorithms; arrhythmia; Arrhythmias, Cardiac - physiopathology; cardiac ailments; cardiac care; cardiac disorder detection; cardiovascular system; clinical decision support system; core diagnostic technique; Devices; Diagnostic systems; diseases; ECG sensor; ECG signals; Echocardiography; electric sensing devices; electrocardiogram signal analysis; Electrocardiography; fatal cardiac events; Humans; life threatening conditions; Medical; medical disorders; medical signal detection; medical signal processing; mobile gateway; Monitoring, Physiologic - instrumentation; Monitoring, Physiologic - methods; myocardial infarction; patient mobile device; patient monitoring; Patients; point‐of‐care device; remote health monitoring system; Remote monitoring; remote server component; Servers; Signal Processing, Computer-Assisted; Special Issue: Computational Models and Methods in Systems Biology and Medicine; Wireless Technology
• ISSN: 1751-8849; 1751-8857
• DOI: 10.1049/iet-syb.2015.0012

Remote health monitoring system with clinical decision support system as a key component could potentially quicken the response of medical specialists to critical health emergencies experienced by their patients. A monitoring system, specifically designed for cardiac care with electrocardiogram (ECG) signal analysis as the core diagnostic technique, could play a vital role in early detection of a wide range of cardiac ailments, from a simple arrhythmia to life threatening conditions such as myocardial infarction. The system that the authors have developed consists of three major components, namely, (a) mobile gateway, deployed on patient's mobile device, that receives 12-lead ECG signals from any ECG sensor, (b) remote server component that hosts algorithms for accurate annotation and analysis of the ECG signal and (c) point of care device of the doctor to receive a diagnostic report from the server based on the analysis of ECG signals. In the present study, their focus has been toward developing a system capable of detecting critical cardiac events well in advance using an advanced remote monitoring system. A system of this kind is expected to have applications ranging from tracking wellness/fitness to detection of symptoms leading to fatal cardiac events.