Embedded Based Health Care System To Predict Cardiac Arrest

Abstract

The concept of connected healthcare systems and smart embedded IoT devices offers the potential for both commercial companies and individuals to benefit. The goal is to use investigations performed on new technologies to enable the creation, enhancement, and expansion of connected health systems to develop a system that can help patients obtain a better awareness of their health status and provide early medical warnings. Cardiac arrest is a chronic disease causing risk of different types of disorders such as hypertension attacks, cerebrovascular attacks, kidney failure and cardiovascular diseases. To prevent such risks, statistics related to cardiac arrest have to be monitored and analyzed in real time. Internet of Things (IoT) assisted fog health monitoring system can be used to monitor blood pressure and to diagnose the cardiac arrest in real time. In United States (US), heart disease and stroke are two of the leading causes of mortality which occur due to high BP. In 2018, nearly 5,10,000 Americans died due to cardiac arrest. US targets to spend $48.6 billion in 2019 on health care support services and medications to treat cardiac arrest. The major chunk of healthcare budget is being spent on Information Technology (IT) based healthcare support services. The vital point of this paper is to continuously generate emergency alerts of blood pressure fluctuation from health monitoring system to heart patient on their mobile phones. Finally, analysis results and compiled medical information of user are stored on cloud storage for sharing with domain experts such as clinicians, doctors and personal caregivers. The temporal information generated from fog layer can be utilized for providing precautionary measures and suggestions well on time for patients’ wellness. Experimental results reveal that proposed framework achieves low response time, high accuracy and bandwidth efficiency.