Chapter 4 - Medical decision support system using data mining: an intelligent health care monitoring system for guarded travel

Abstract

Protracted driving causes physical mental stress that increases life in higher-risk state and it takes health to all negative issues. Spending more time on driving a vehicle governs a long, uninterrupted session that leads to obesity, risk to mental health, lack of sleep, bad habits like addictions have changed the quality of life. In this research work, a reliable emergency service ensures a safe driving experience. Such experience guarantees the continual monitoring of the driver's health condition in smart manner. In order to monitor the driver's heart rate, an intelligent healthcare system is proposed that utilizes an artificial recurrent neural network (RNN) model which continually monitors driver's health condition and persistently update to the cloud server. However, tracking their health status is a complex task because health condition statuses are varied and hence this leads to the essential creation of optimized Electronic Health Record (EHR). To accomplish a reliable emergency service, the proposed proximity-based communication model transmits the critical condition record to the service providers even without Internet capability. The long-short term memory is capable of learning the driver's behavior continually in long-term decencies of his/her activity which converts sensor reading into optimized EHR. These health readings are generated from various external body sensors. The proposed work would be noticed as one step toward guaranteed guarded journey. The experimental results achieved 94.65% accuracy of higher prediction rate.