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MSPM: A Multi-Site Physiological Monitoring Dataset for Remote Pulse, Respiration, and Blood Pressure Estimation
We provide thorough experiments demonstrating the suitability of MSPM to support research on rPPG, respiration rate, and PTT.
Full-Body Cardiovascular Sensing with Remote Photoplethysmography
In this paper we explored the feasibility of rPPG from non-face body regions such as the arms, legs, and hands.
Hallucinated Heartbeats: Anomaly-Aware Remote Pulse Estimation
Extensive experimentation with eight research datasets (rPPG-specific: DDPM, CDDPM, PURE, UBFC, ARPM; deep fakes: DFDC; face presentation attack detection: HKBU-MARs; rPPG outlier: KITTI) show better accuracy of anomaly detection for deep learning models incorporating the proposed training (75. 8%), compared to models trained regularly (73. 7%) and to hand-crafted rPPG methods (52-62%).
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