Heart Rate

Heart rate (HR) monitoring is a crucial aspect of healthcare, with research focusing on accurate and efficient measurement methods for various applications, from continuous health tracking to early disease detection. Current research employs diverse approaches, including deep learning models (e.g., convolutional neural networks, transformers, diffusion models) and signal processing techniques to extract HR from various sources like electrocardiograms (ECGs), photoplethysmography (PPG), seismocardiograms (SCGs), and even facial videos or abdominal audio. These advancements are improving the accuracy, accessibility, and cost-effectiveness of HR monitoring, leading to potential improvements in personalized healthcare and remote patient monitoring.