REAL TIME RISK PREDICTION OF HEART PATIENTS USING HRV AND IOT

Heart problems refer to any condition that affects the heart’s ability to function properly, which can range from minor to severe. Common heart problems are : Coronary artery disease, Heart attack, Arrhythmia, Heart failure, Valvular heart disease, Congenital heart defects, Hypertension,etc. Heart Rate Variability (HRV) is a measure of the variation in time between successive heartbeats. HRV analysis can help to evaluate the balance between the sympathetic and parasympathetic nervous systems, which can give valuable insights into a person’s overall health and their risk of developing heart problems. In this project, we have used components such as Temperature sensor, Pulse Oxi-meter sensor and ECG sensor to measure patients heart health. By leveraging the power of machine learning, the system predict risk of patients heart health. While HRV analysis can provide useful information, it should not be considered a solution or treatment for heart problems. Rather, HRV analysis can be used in conjunction with other diagnostic tools to assess a person’s heart health and identify potential risk factors.