A proposed heart attack self-test mobile application aims to provide accurate risk detection by considering multiple symptom parameters without the intervention of a medical specialist.
The paper proposes a conceptual mobile health system integrating physiological sensors and symptom questionnaires to predict heart attack risk.
In the recent years, heart attack has become an alarming disease. Heart diseases have become one of the leading causes of death. In India, the number of deaths caused by heart attacks is about 25% of the total death. This happens due to the delay in detecting the symptoms or lack of early diagnosis. This can be avoided by integrating mobile computing technologies with health care systems, which will lead to detect abnormal heart rates and predict heart attacks before it occurs. Heart disease is a major cause of morbidity in the modern society. The earlier system detect the risk of heart attack using only limited parameter which are ECG, pulserate. Hence it cannot guarantee the risk for other symptoms like left shoulder pain, chest pain and etc. So the proposed system did consider all the parameter which can be a symptom of heart attack and hence provide a accurate risk detection system. The proposed system describes a heart attack self-test mobile application that allows potential victims, without the intervention of any medical specialist, to quickly assess whether they are having a heart attack.
Chandurkar et al. (Thu,) conducted a other in Heart attack. Heart attack self-test mobile application vs. Earlier systems using limited parameters (ECG, pulse rate) was evaluated on Accurate risk detection of heart attack. A proposed heart attack self-test mobile application aims to provide accurate risk detection by considering multiple symptom parameters without the intervention of a medical specialist.