Tricam-rPPG: A Multimodal Multispectral Dataset for remote Photoplethysmography

This paper introduces Tricam-rPPG, a multimodal datasetdesigned to support systematic studies of remote photoplethysmography(rPPG) using multispectral imaging. Remote (noncontact) monitoringoffers the potential for unobtrusive measurement of physiological signalsrelated to health, cognitive load, and affect. However, most existing rPPGdatasets rely primarily on RGB imaging, limiting the study of spectraleffects, illumination variability, and sensing biases associated with differ-ences in optical properties of the skin. Tricam-rPPG provides synchro-nized recordings of 31 human subjects from three co-located cameras: astandard RGB camera and two near-infrared (NIR) cameras operatingat 850 nm and 940 nm, all captured under controlled illumination con-ditions. For fourteen participants, simultaneous recordings from MetaAria glasses are also included. All cases are supplemented by referencewaveforms of blood volume pulses (BVP) measured using a fingertipPPG sensor. In addition to presenting the dataset, we establish base-line benchmarks with widely used rPPG algorithms to evaluate heart-rate estimation performance across different combinations of spectralchannels. By providing synchronized RGB and NIR video together withphysiological ground truth, Tricam-rPPG enables new research directionsin multispectral physiological sensing, fairness-aware rPPG algorithms,and robust remote cardiovascular monitoring. The dataset is availableunder a data use license and mutual agreement (check https://tricam-rppg.github.io).