Biomedical Signal Processing For Heart Rate Variability

Abstract

The significance of HRV in science and heart health is becoming increasingly evident as study on it expands.  Artificial intelligence, machine learning techniques, and frequency domain analysis of HRV have the ability to significantly impact people's life quickly if they are accurate. That's why researchers are constantly refining these methods to enhance patient health, reduce the risk of road accidents, and improve overall quality of life. Many researchers are actively focusing on ambulatory detection of HRV in order to dramatically and favorably impact the health and well-being of individuals dealing with chronic stress, diabetes, hypertension, cardiovascular disease (CVD), and myocardial infarction.  To prevent major health emergencies, it is imperative that these patients be watched all day.  For elderly or chronically ill patients with cardiovascular problems who find it difficult to visit hospitals on a regular basis because of physical limitations and distance, remote HRV monitoring could be a game-changer.