Design of Remote Heart Monitoring System for Cardiac Patients.

At present, the people monitoring, in particular outside clinical sites, has become a major research concern. With the rapid technological advances, remote monitoring is considered as a vital component of future e-Health systems. The techniques of the Internet of Things (IoT) offer the opportunity to change the nature of health services in an omnipresent way, and to create them based on the patients’ physical condition rather than their feelings. Nevertheless, these new technologies have also made this area more difficult to manage and manipulate. In this paper, we proposed a monitoring system that can send and analyze the collected real-time data for effective decision-making in the case of Remote Cardiac Patients. We propose to design and develop a Remote Heart Monitoring System (RHMS) that combines two complementary technologies (1) machine learning for generating intelligent valuable information, and (2) visual analytics for gaining insight the collected real-time data. The success of these systems is based on the quality of their design and development. For this reason, we propose to use the multi-agent architecture. The developed prototype was evaluated by 30 participants to verify its feasibility. It has been validated in terms of utility and usability, RHMS time of response and multi-agent modeling quality. The multi-agent modeling of a RHMS based on automatic and interactive machine learning (visual data mining) presented interesting results. It is a distributed architecture of a real-time monitoring system for cardiac patients helping remote monitors to improve the management of their out-of-hospital data.