Evaluating remote photoplethysmography: A 10-minute video dataset in uncontrolled lighting.

Remote photoplethysmography (rPPG) is a technique that enables the extraction of physiological parameters, such as heart rate, from video recordings in a completely non-contact manner. Although widely studied, rPPG research has been hindered by the scarcity of long-duration and complex video datasets recorded in realistic, everyday scenarios. In this work, we present a dataset comprising 10-minute facial video recordings of 26 participants, along with recorded electrocardiograms (ECG) used as a reference signal. The recordings were acquired using a low-cost RGB webcam and a research-grade ECG monitor, under natural daylight and uncontrolled ambient lighting conditions. Videos were manually synchronized with the ECG and cropped to a 64 × 64 pixel resolution to ensure subject anonymization. While participants were predominantly young Portuguese university students, and Fitzpatrick skin types I-IV are represented, this limits generalizability to broader populations. Each recording includes auxiliary metadata such as temperature, humidity, and illumination levels measured at the beginning and end of the session. The dataset aims to support the development and benchmarking of rPPG algorithms under realistic webcam conditions. Baseline heart rate estimations using standard rPPG methods are also provided.