2026
doi: 10.12720/jait.17.4.788-799
Enhancing Heart Rate Estimation with POS-SSA Remote Photoplethysmography
Ruixuan Wang1,*
,
Wei Quan1 ,
Bogdan Matuszewski1 ,
Nick A. Heywood2 ,
Christopher Gaffney3 ,
Katie Hoad3
- 1School of Engineering and Computing, University of Lancashire, Preston, United Kingdom
- 2East Lancashire Hospitals, NHS Trust, Blackburn, United Kingdom
- 3Lancaster Medical School, Lancaster University, Lancaster, United Kingdom
- Manuscript receivedNovember 1, 2025
- revisedDecember 4, 2025
- acceptedJanuary 27, 2026
- publishedApril 24, 2026
Abstract
Remote Photoplethysmography (rPPG) enables non-contact heart rate monitoring from facial videos but it is highly susceptible to motion artefacts, illumination changes, and sensor noise. A framework combining the Plane Orthogonal-to-Skin (POS) method and Singular Spectrum Analysis (SSA) was proposed in this work to address these challenges by first projecting normalized Red Green Blue (RGB) signals onto a skin-tone–orthogonal subspace to suppress illumination and motion distortions and then decomposing the resulting signal into components that isolate physiologically meaningful oscillations. Evaluation on the PFF and UBFC-Phys dataset demonstrates that this approach consistently outperforms conventional single-channel, statistical, and chrominance-based methods by achieving a mean absolute error of 4.99 beats per minute (bpm) and correlation of 0.76 on PFF, and a mean absolute error of 4.11 bpm with correlation of 0.86 on UBFC-Phys. Furthermore, the comparison with results reported in the existing literature indicates that the proposed framework achieves competitive accuracy relative to popular learning-based rPPG approaches. These findings indicate that integrating chrominance projection with adaptive temporal decomposition significantly improves robustness and accuracy for contact-free heart rate estimation.
Keywords
- facial video-based remote Photoplethysmography (rPPG)
- Plane Orthogonal-to-Skin (POS)
- Singular Spectrum Analysis (SSA)
How to Cite
Ruixuan Wang, Wei Quan, Bogdan Matuszewski, Nick A. Heywood, Christopher Gaffney, and Katie Hoad, "Enhancing Heart Rate Estimation with POS-SSA Remote Photoplethysmography," Journal of Advances in Information Technology, vol. 17, no. 4, pp. 788-799, 2026. https://doi.org/10.12720/jait.17.4.788-799
Copyright & License
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
