Passive heart-rate monitoring during smartphone use in everyday life (www.nature.com)

Researchers have developed a groundbreaking deep-learning system for passive heart-rate monitoring (PHRM) using facial video-based photoplethysmography via smartphones. This approach enables continuous tracking of heart rate (HR) and resting heart rate (RHR) during routine smartphone usage, eliminating the need for wearables, which often restrict access to heart health data. Using a dataset of over 192,000 videos from a diverse group of participants, PHRM demonstrated superior accuracy in HR measurement, achieving a mean absolute percentage error (MAPE) below 10% compared to traditional electrocardiograms. Crucially, it maintained consistent performance across various skin tones, addressing significant disparities in existing heart health technologies. The significance of this development lies in its potential to democratize cardiovascular monitoring, as smartphones are widely adopted and used daily by nearly 90% of adults in the U.S. and 69% globally. By validating PHRM in both laboratory and real-world settings, the study not only advances the field of remote heart monitoring but also emphasizes the importance of inclusivity in tech solutions. The researchers are releasing both the pre-trained model and the extensive annotated video dataset to encourage further exploration and innovation in passive health monitoring systems, positioning smartphones as key tools for managing cardiovascular health effectively and equitably.