The reliability of remote photoplethysmography under low illumination and elevated heart rates.

ABSTRACT: Remote photoplethysmography (rPPG) offers a non-invasive means of estimating heart rate in telemedicine settings. Yet its reliability remains uncertain due to the limited diversity and ecological validity of existing benchmark datasets. In this work, we systematically investigate the robustness of rPPG methods under challenging conditions, specifically low illumination and elevated heart rates. We introduce the CHILL dataset, which comprises video and PPG signals collected from 45 participants across two lighting conditions (bright and dark) and exercise-induced heart rates ranging from 54 to 141 beats per minute. We assessed eight rPPG algorithms, including four signal processing-based and four deep learning-based approaches, across three datasets: the newly collected CHILL dataset and tw

SUBMITTER: Acharya B 

PROVIDER: S-EPMC12678791 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature