Non-Contact Health Monitoring During Daily Personal Care Routines
Journal:
arXiv
Published Date:
Jun 11, 2025
Abstract
Remote photoplethysmography (rPPG) enables non-contact, continuous monitoring
of physiological signals and offers a practical alternative to traditional
health sensing methods. Although rPPG is promising for daily health monitoring,
its application in long-term personal care scenarios, such as mirror-facing
routines in high-altitude environments, remains challenging due to ambient
lighting variations, frequent occlusions from hand movements, and dynamic
facial postures. To address these challenges, we present LADH (Long-term
Altitude Daily Health), the first long-term rPPG dataset containing 240
synchronized RGB and infrared (IR) facial videos from 21 participants across
five common personal care scenarios, along with ground-truth PPG, respiration,
and blood oxygen signals. Our experiments demonstrate that combining RGB and IR
video inputs improves the accuracy and robustness of non-contact physiological
monitoring, achieving a mean absolute error (MAE) of 4.99 BPM in heart rate
estimation. Furthermore, we find that multi-task learning enhances performance
across multiple physiological indicators simultaneously. Dataset and code are
open at https://github.com/McJackTang/FusionVitals.
