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Influence of Skin Tone on Efficiency of Vision-Based Heart Rate Estimation

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Book cover Recent Developments and Achievements in Biocybernetics and Biomedical Engineering (PCBBE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 647))

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Abstract

Non-contact methods of human heart rate (HR) facilitate medical assessment of this most important vital sign and increase patient comfort. Videoplethysmograpy (VPG) can be applied not only in healthcare units but also at homes and remote locations. In this paper the efficiency of an algorithm for pulse rate detection based on face image is analyzed. The correspondence between patient ethnicity and various color components used for HR estimation is examined. The results suggest that analysis of color components related to red provide better performance in case of darker skin tone, while green-related components are more accurate for persons of Caucasian origin.

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References

  1. Przybyło, J., Kańtoch, E., Jabloński, M., Augustyniak, P.: Distant measurements of plethysmographic signal in various lighting conditions using configurable frame-rate camera. Metrol. Meas. Syst. 23(4), 579–592 (2016)

    Google Scholar 

  2. Lam, A., Kuno, Y.: Robust heart rate measurement from video using select random patches. In: 2015 IEEE International Conference on Computer Vision, Santiago, pp. 3640–3648 (2015)

    Google Scholar 

  3. Lewandowska, M., Rumiński, J., Kocejko, T.: Measuring pulse rate with a webcam – a non-contact method for evaluating cardiac activity. In: Proceedings of the Federated Conference on Computer Science and Information Systems, pp. 405–410 (2011)

    Google Scholar 

  4. Prance, R.J., Beardsmore-Rust, S., Watson, P., Harland, C.J., Prance, H.: Remote detection of human electrophysiological signals using electric potential sensors. Appl. Phys. Lett. 93(3), 033906–3 (2008)

    Article  Google Scholar 

  5. Obeid, D., Sadek, S., Zaharia, G., Zein, G.E.: Multitunable microwave system for touchless heartbeat detection and heart rate variability extraction. Microw. Opt. Technol. Lett. 52(10), 192–198 (2010)

    Article  Google Scholar 

  6. Boric-Lubecke, O., Lubecke, V.M., Mostafanezhad, I., Park, B.K., Massagram, W., Jokanovic, B.: Doppler radar architectures and signal processing for heart rate extraction. Mikrotalasna Revija. 15(2), 12–17 (2009)

    Google Scholar 

  7. Morbiducci, U., Scalise, L., Melis, M.D., Grigioni, M.: Optical vibrocardiography: a novel toll for the optical monitoring of cardiac activity. Ann. Biomed. Eng. 35(1), 45–58 (2007)

    Article  Google Scholar 

  8. Gault, T.R., Farag, A.A.: A fully automatic method to extract the heart rate from thermal video. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 336–341 (2013)

    Google Scholar 

  9. Mesleh, A., Skopin, D., Baglikov, S., Quteisah, A.: Heart rate extraction from vowel speech signals. J. Comput. Sci. Technol. 27(6), 1243–1251 (2012)

    Article  Google Scholar 

  10. Verkruysse, W., Svaasand, L.O., Nelson, J.S.: Remote plethysmographic imaging using ambient light. Opt. Express. 16(26), 21434–21445 (2008)

    Article  Google Scholar 

  11. Poh, M.Z., McDuff, D.J., Picard, R.W.: Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Opt. Express. 18(10), 10762–10774 (2010)

    Article  Google Scholar 

  12. Sun, Y., Hu, S., Azorin-Peris, V., Greenwald, S., Chambers, J., Zhu, Y.: Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory. J. Biomed. Opt. 16(7), 077010 (2011)

    Article  Google Scholar 

  13. Qi, H., Wang, J., Miao, C.H.: Non-contact driver cardiac physiological monitoring using video data. CHINA SIP, pp. 418–422 (2015)

    Google Scholar 

  14. Zhang, Q., Wu, Q., Zhou, Y., Wu, X., Ou, Y., Zhou, H.: Webcam-based, non-contact, real time measurement for the physiological parameters of drivers. Measurement 100, 311–321 (2017)

    Article  Google Scholar 

  15. Qi, H., Guo, Z., Chen, X., Shen, Z., Wang, Z.J.: Video-based human heart rate measurement using joint blind source separation. Biomed. Sig. Proc. Control 3, 309–320 (2017)

    Article  Google Scholar 

  16. Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, vol. 1, pp. 511–518 (2001)

    Google Scholar 

  17. Angelopoulou, E.: The reflectance spectrum of human skin. Scholarly Commons, University of Pensylvania (1999)

    Google Scholar 

  18. Park, H.: Relative-error and Generalized Prediction Rules. North Carolina State University (1994)

    Google Scholar 

  19. Stehman, S.V.: Selecting and interpreting measures of thematic classification accuracy. Remote Sens. Environ. 62(1), 77–89 (1997)

    Article  Google Scholar 

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Authors and Affiliations

  1. Institute of Electronics, Lodz University of Technology, ul. Wólczańska 211/215, 90-924, Łódź, Poland

    Aleksandra Królak

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  1. Aleksandra Królak
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Correspondence to Aleksandra Królak .

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Editors and Affiliations

  1. AGH University of Science and Technology, Krakow, Poland

    Piotr Augustyniak

  2. Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland

    Roman Maniewski

  3. AGH University of Science and Technology, Krakow, Poland

    Ryszard Tadeusiewicz

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Królak, A. (2018). Influence of Skin Tone on Efficiency of Vision-Based Heart Rate Estimation. In: Augustyniak, P., Maniewski, R., Tadeusiewicz, R. (eds) Recent Developments and Achievements in Biocybernetics and Biomedical Engineering. PCBBE 2017. Advances in Intelligent Systems and Computing, vol 647. Springer, Cham. https://doi.org/10.1007/978-3-319-66905-2_4

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  • DOI: https://doi.org/10.1007/978-3-319-66905-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66904-5

  • Online ISBN: 978-3-319-66905-2

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