Intelligent health monitoring system modeling based on machine learning and agent technology

Abstract

The use of machine learning approach in the field of health informatics improves the quality and effectiveness of decision-making process. Its particular integration into the Remote Health Monitoring Systems (RHMS) allows: collecting, analyzing and learning from real-time data, automatically gainin g knowledge and making predictions on the patients state. The RHMS represent an effective solution to control and monitor a growing number of dependent or elderly patients. They showed impressive results in healthcare applications. These systems are built around the sensors installed on the body of the patient and others embedded in their environments. In this context, we are confronted with the challenge of temporal aspect of data. To meet this challenge, we propose that RHMS combine machine learning for generating intelligent valuable information, and visual analytics for gaining insight the collected real-time data. The success of these applications is based on the quality of their design and development. For this reason, we propose to design a RHMS using multi-agent technology. The developed prototype was evaluated to verify our proposal feasibility.