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Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44575, first published .
Close-up of a man's face with a blue outline around his lower face and chin.

Dynamic Region of Interest Selection in Remote Photoplethysmography: Proof-of-Concept Study

Dynamic Region of Interest Selection in Remote Photoplethysmography: Proof-of-Concept Study

Journals

  1. van Putten L, Bamford K, Veleslavov I, Wegerif S. From video to vital signs: using personal device cameras to measure pulse rate and predict blood pressure using explainable AI. Discover Applied Sciences 2024;6(4) View
  2. Saikevičius L, Raudonis V, Dervinis G, Baranauskas V. Non-Contact Vision-Based Techniques of Vital Sign Monitoring: Systematic Review. Sensors 2024;24(12):3963 View
  3. Xiang G, Ou Y, Li J, Wang L, Hu Y, Wang X, Wu X, Peng Y. Recovering Physiological Signals From Facial Videos: Recent Advances and Applications in Intelligent Vehicles. IEEE Transactions on Intelligent Vehicles 2024;9(10):6576 View
  4. van Putten L, Ahmed A, Wegerif S. Remote photoplethysmography for contactless pulse rate monitoring: algorithm development and accuracy assessment. Physiological Measurement 2025;46(11):115004 View
  5. Woelk S, Garfinkel S, Mayiwar L, Knöferle K. Advancing remote photoplethysmography (rPPG) to facilitate cardiac monitoring in naturalistic settings using webcam technology. Behavior Research Methods 2026;58(5) View
  6. Ostrysz M. Non-invasive monitoring of human vital signs under dynamic conditions: A review of acoustic, optical and ballistocardiographic methods. Pervasive and Mobile Computing 2027;124:102290 View

Conference Proceedings

  1. van Putten L, Bamford K. 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). Improving Systolic Blood Pressure Prediction from Remote Photoplethysmography Using a Stacked Ensemble Regressor View
  2. Susi A, Akila V, Govindasamy V. 2025 IEEE 1st International Conference on Smart and Sustainable Developments in Electrical Engineering (SSDEE). Examination of Signal-to-Noise Ratio in Remote Photoplethysmography Signal Extraction for Video Authenticity Detection View
  3. Si M, Yang S, Shen C. 2026 9th International Conference on Computer Network, Electronic and Automation (ICCNEA). Physiological Reliability-Aware Self-Supervised rPPG for Heart Rate Monitoring View