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Original Article
Implementation Paper on Contactless Heart-Beat Detection Using Image Processing
Shalini Ranjan1
Sanika Shingare2
Daksh H Umesh3
Rohith G N4
1Assistant Professor, Department of Computer Science and Design Engineering, Dayananda Sagar Academy of Technology & Management, Bengaluru, Karnataka, India. 234 Undergraduate Students, Department of Computer Science and Design Engineering, Dayananda Sagar Academy of Technology & Management, Bengaluru, Karnataka, India.
Published Online: May-August 2025
Pages: 01-07
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20250402001
References
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11. M.-A. Fiedler, P. Werner, M. Rapczyński, and A. Al-Hamadi, “Deep face segmentation for improved heart and respiratory rate
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Journal of Ambient Intelligence and Humanized Computing, vol. 14, no. 7, pp. 9383–9402, 2023.
https://link.springer.com/article/10.1007/ s12652-023-04346-2
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21445, 2008. https://www.osapublishing.org/oe/fulltext.cfm?uri=oe-16-26-21434&id=170899
13. T. Zhang, W. Zheng, Z. Cui, Y. Zong, J. Yan, and K. Yan, “A deep neural network-driven feature learning method for multi-view
facial expression recognition,” IEEE Transactions on Multimedia, vol. 18, no. 12, pp. 2528–2536, 2016.
https://ieeexplore.ieee.org/document/7524821
14. H. Y. Wu, M. Rubinstein, E. Shih, J. Guttag, F. Durand, and W. Freeman, “Eulerian video magnification for revealing subtle changes
in the world,” in
ACM Transactions on Graphics, vol. 31, no. 4, pp. 65:1–65:8, 2012. https://dl.acm.org/doi/10.1145/2185520.2185561
15. M. Soleymani, J. Lichtenauer, T. Pun, and M. Pantic, “A multimodal database for affect recognition and implicit tagging,” IEEE
Transactions on Affective Computing, vol. 3, no. 1, pp. 42–55, 2012. https://ieeexplore.ieee.org/document/6122305
16. X. Yu et al., “Non-contact remote measurement of heart rate variability using near-infrared photoplethysmography imaging,” in
IEEE Engineering in
Medicine and Biology Society (EMBC), 2018. https://ieeexplore.ieee.org/document/8512530
17. R. M. Fouad, O. A. Omer, and M. H. Aly, “Optimizing remote photoplethysmography using adaptive skin segmentation for real-
time heart rate monitoring,” IEEE Access, vol. 7, pp. 76513–76528, 2019. https://ieeexplore.ieee.org/document/8713885
Based Embedded Platforms,” Sensors, vol. 23, no. 3507, pp. 1–15, 2023. https://www.mdpi.com/1424-8220/23/7/3507
2. M. A. Hassan, A. S. Malik, N. Saad, B. Karasfi, Y. S. Ali, and D. Fofi, “Optimal source selection for image photoplethysmography,” in
Proceedings of
IEEE International Conference on Instrumentation and Measurement Technology, pp. 1–5, 2016.
https://ieeexplore.ieee.org/document/7532987
3. X. Li, J. Chen, G. Zhao, and M. Pietikäinen, “Remote heart rate measurement from face videos under realistic situations,” in IEEE
Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4264–4271, 2014. https://ieeexplore.ieee.org/document/6909716
4. D. McDuff, S. Gontarek, and R. W. Picard, “Improvements in remote cardiopulmonary measurement using a five-band digital
camera,” IEEE
Transactions on Biomedical Engineering, vol. 61, no. 10, pp. 2593–2601, Oct. 2014. https://ieeexplore.ieee.org/document/6832435
5. D. Shao, Y. Yang, C. Liu, F. Tsow, H. Yu, and N. Tao, “Noncontact monitoring breathing pattern, exhalation flow rate and pulse
transit time,” IEEE Transactions on Biomedical Engineering, vol. 61, no. 11, pp. 2760–2767, Nov. 2014.
https://ieeexplore.ieee.org/document/6879547
6. M. van Gastel, S. Stuijk, and G. de Haan, “New principle for measuring arterial blood oxygenation, enabling motion-robust
remote monitoring,”
Scientific Reports, vol. 6, Dec. 2016. https://www.nature.com/articles/srep38609
7. L. Kong et al., “Non-contact detection of oxygen saturation based on visible light imaging device using ambient light,” Optics Express,
vol. 21, no. 15, p. 17464, Jul. 2013. https://www.osapublishing.org/oe/fulltext.cfm?uri=oe-21-15-17464&id=259036
8. A. Moço and W. Verkruysse, “Pulse oximetry based on photoplethysmography imaging with red and green light,” Journal of Clinical
Monitoring and
Computing, Jan. 2020. https://link.springer.com/article/10.1007/s10877-019-00331-1
9. J. Fei and I. Pavlidis, “Thermistor at a distance: Unobtrusive measurement of breathing,” IEEE Transactions on Biomedical
Engineering, vol. 57, no. 4,
pp. 988–998, Apr. 2009. https://ieeexplore.ieee.org/document/4807342
10. J. Deng, J. Guo, E. Ververas, I. Kotsia, and S. Zafeiriou, “Retinaface: Single-shot multi-level face localisation in the wild,” in IEEEConference on Computer Vision and Pattern Recognition (CVPR), 2020. https://ieeexplore.ieee.org/document/9156610
11. M.-A. Fiedler, P. Werner, M. Rapczyński, and A. Al-Hamadi, “Deep face segmentation for improved heart and respiratory rate
estimation from videos,”
Journal of Ambient Intelligence and Humanized Computing, vol. 14, no. 7, pp. 9383–9402, 2023.
https://link.springer.com/article/10.1007/ s12652-023-04346-2
12. W. Verkruysse, L. O. Svaasand, and J. S. Nelson, “Remote plethysmographic imaging using ambient light,” Optics Express, vol. 16, no.
26, pp. 21434–
21445, 2008. https://www.osapublishing.org/oe/fulltext.cfm?uri=oe-16-26-21434&id=170899
13. T. Zhang, W. Zheng, Z. Cui, Y. Zong, J. Yan, and K. Yan, “A deep neural network-driven feature learning method for multi-view
facial expression recognition,” IEEE Transactions on Multimedia, vol. 18, no. 12, pp. 2528–2536, 2016.
https://ieeexplore.ieee.org/document/7524821
14. H. Y. Wu, M. Rubinstein, E. Shih, J. Guttag, F. Durand, and W. Freeman, “Eulerian video magnification for revealing subtle changes
in the world,” in
ACM Transactions on Graphics, vol. 31, no. 4, pp. 65:1–65:8, 2012. https://dl.acm.org/doi/10.1145/2185520.2185561
15. M. Soleymani, J. Lichtenauer, T. Pun, and M. Pantic, “A multimodal database for affect recognition and implicit tagging,” IEEE
Transactions on Affective Computing, vol. 3, no. 1, pp. 42–55, 2012. https://ieeexplore.ieee.org/document/6122305
16. X. Yu et al., “Non-contact remote measurement of heart rate variability using near-infrared photoplethysmography imaging,” in
IEEE Engineering in
Medicine and Biology Society (EMBC), 2018. https://ieeexplore.ieee.org/document/8512530
17. R. M. Fouad, O. A. Omer, and M. H. Aly, “Optimizing remote photoplethysmography using adaptive skin segmentation for real-
time heart rate monitoring,” IEEE Access, vol. 7, pp. 76513–76528, 2019. https://ieeexplore.ieee.org/document/8713885
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