An Internet of Things (IoT) Application for Predicting the Quantity of Future Heart Attack Patients

Now days the heart disease is the leading cause of death worldwide. It is a complex task to predict the heart attack for a medical practitioner since it is required more experience and knowledge. However, heart rate monitoring is the most important scale of measurement that is the influence factor for heart attack with other health fitness like blood pressure, serum cholesterol and level of blood sugar. In the era of rapid revolution of Internet of things (IoT), the sensors for monitoring heart rate are growing in availability to patients. In this paper, I explained the architecture for heart rate and other data monitoring technique and I also explained how to use a machine learning technique like kNN classification algorithm to predict the heart attack by using the collected heart rate data and other health related perimeter.

[1]  Amy Loutfi,et al.  Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges , 2013, Sensors.

[2]  Kevin C. Desouza,et al.  Data mining in healthcare information systems: case study of a veterans' administration spinal cord injury population , 2003, 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the.

[3]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[4]  V. Ranjani,et al.  Data Mining Applications In Healthcare Sector: A Study , 2013 .

[5]  Cem Ersoy,et al.  Wireless sensor networks for healthcare: A survey , 2010, Comput. Networks.

[6]  Wei Zhao,et al.  Medical application on Internet of Things , 2011 .

[7]  Wahidah Husain,et al.  Data Mining in Healthcare – A Review , 2015 .

[8]  Rajkumar Buyya,et al.  Internet of Things: An Overview , 2017, ArXiv.

[9]  Mohammad Ashraf Bani Ahmad Mining Health Data for Breast Cancer Diagnosis Using Machine Learning , 2013 .

[10]  Kyung Sup Kwak,et al.  Security and Privacy Issues in Wireless Sensor Networks for Healthcare Applications , 2010, Journal of Medical Systems.

[11]  Soni Jyoti,et al.  Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction , 2011 .

[12]  A. Iskandrian,et al.  Major risk factors for cardiovascular disease: debunking the "only 50%" myth. , 2003, JAMA.

[13]  P. Stein,et al.  Heart rate variability: a measure of cardiac autonomic tone. , 1994, American heart journal.

[14]  Mosima Anna Masethe,et al.  Prediction Of Heart Disease Using Classification Algorithms , 2020 .

[15]  Oana Geman,et al.  An Approach of a Decision Support and Home Monitoring System for Patients with Neurological Disorders using Internet of Things Concepts , 2014 .

[16]  D. Mozaffarian,et al.  Executive Summary: Heart Disease and Stroke Statistics—2015 Update A Report From the American Heart Association , 2011, Circulation.