Publication Type:

Conference Paper


Advances in Signal Processing and Intelligent Recognition Systems, Springer International Publishing, Volume 425, Cham, p.485-500 (2016)




The proposed work suggests the design of a health care system that provides various services to monitor the patients using wireless technology. It is an intelligent Remote Patient monitoring system which is integrating patient monitoring with various sensitive parameters, wireless devices and integrated mobile and IT solutions. This system mainly provides a solution for heart diseases by monitoring heart rate and blood pressure. It also acts as a decision making system which will reduce the time before treatment. Apart from the decision-making techniques, it generates and forwards alarm messages to the relevant caretakers by means of various wireless technologies. The proposed system suggests a framework for measuring the heart rate, temperature and blood pressure of the patient using a wearable gadget and the measured parameters is transmitted to the Bluetooth enabled Android smartphone. The various parameters are analyzed and processed by android application at client side. The processed output is transferred to the server side in a periodic interval. Whenever an emergency caring arises, an alert message is forwarded to the various care providers by the client side application. The use of various wireless technologies like GPS, GPRS, and Bluetooth leads us to monitor the patient remotely. The system is said to be an intelligent system because of its diagnosis capability, timely alert for medication etc. The current statistics shows that heart disease is the leading cause of death and which shows the importance of the technology to provide a solution for reducing the cardiac arrest rate. Apart from that the proposed work compares different algorithms and proposes the usage of Random Forest algorithm for heart disease prediction.

Cite this Research Publication

S. S., S., R., and Jisha R. C., “A Real Time Patient Monitoring System for Heart Disease Prediction Using Random Forest Algorithm”, in Advances in Signal Processing and Intelligent Recognition Systems, Cham, 2016, vol. 425, pp. 485-500.