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Non-invasive Measurement of Human Pulse Based on Photographic Images of the Face

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Information Technology in Biomedicine (ITIB 2022)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1429))

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Abstract

The focus of this study was to test a contactless photoplethysmography based method to calculate pulse of a patient from a video recording of their face. For this purpose deep convolution neural network was used for detection the region of interest skin area of face and then analyzing of the variability of the image values was processed as a signal in frequency domain for pulse reconstruction. The method was tested on three video sets with different video resolutions: 1920 \(\times \) 1080 px, 960 \(\times \) 540 px, and 640 \(\times \) 580 px. The best results came from a set with a resolution of 960 \(\times \) 540 px, with a relative error of 10.6%, and an absolute error of 10.4 BPM, and a processing speed of 3.7 FPS. The method can be useful when it is impossible to use dedicated medical equipment to measure the human pulse.

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References

  1. Allen, J.: Photoplethysmography and its application in clinical physiological measurement. https://doi.org/10.1088/0967-3334/28/3/R01

  2. Cheng, Z., et al.: Noninvasive monitoring of blood pressure using optical Ballistocardiography and Photoplethysmograph approaches. In: 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (2013). https://doi.org/10.1109/EMBC.2013.6610029

  3. FaceLib library documentation. https://github.com/sajjjadayobi/FaceLib. Accessed 24 Jan 2022

  4. Heusch, G., Anjos, A., Marcel, S.: A Reproducible Study on Remote Heart Rate Measurement. CoRR (2017). db/journals/corr/corr1709.html#abs-1709-00962

    Google Scholar 

  5. Jones, D.: The Blood Volume Pulse - Biofeedback Basics (2018). https://www.biofeedback-tech.com/articles/2016/3/24/the-blood-volume-pulse-biofeedback-basics. Accessed 24 Jan 2022

  6. Lamba, P.S., Virmani, P.: Contactless heart rate estimation in humans using low cost face video. J. Stat. Manage. Syst. 23(7) (2020). https://doi.org/10.1080/09720510.2020.1799584. Intelligent Decision Making using Best Practices of Big Data Technologies (Part-II)

  7. Liu, X., Zao, Y., Kuang, H., Ma, X.: Face image age estimation based on data augmentation and lightweight convolutional neural network. In: Symmetry 2020. https://doi.org/10.3390/sym12010146

  8. Nair, B.K., Lokhande, S.S.: Patient monitoring system using image processing. Int. J. Adv. Res. Electr. Electron. Instrum. Eng. (2017). https://doi.org/10.15662/IJAREEIE.2017.0606127

  9. Nelson, B.W., Allen, N.B.: Accuracy of Consumer Wearable Heart Rate Measurement During an Ecologically Valid 24-Hour Period: Intraindividual Validation Study (2019). https://doi.org/10.2196/10828

  10. Omar, C., et al.: Accuracy of Pulse Oximetry Measurement of Heart Rate of Newborn Infants in the Delivery Room (2008). https://doi.org/10.1016/j.jpeds.2008.01.002

  11. rPPG library documentation. https://github.com/nasir6/rPPG. Accessed 24 Jan 2022

  12. Yu, Z., Peng, W., Li, X., Hong, X., Zhao, G.: Remote heart rate measurement from highly compressed facial videos: an end-to-end deep learning solution with video enhancement. In: IEEE/CVF International Conference on Computer Vision, pp. 151–160 (2019). https://doi.org/10.1109/ICCV.2019.00024

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Author information

Authors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, ul. Roosevelta 40, 41-800, Zabrze, Poland

    Jakub Gumulski, Marta Jankowska & Dominik Spinczyk

Authors
  1. Jakub Gumulski
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  2. Marta Jankowska
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  3. Dominik Spinczyk
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Corresponding author

Correspondence to Dominik Spinczyk .

Editor information

Editors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Ewa Pietka

  2. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Pawel Badura

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Jacek Kawa

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Wojciech Wieclawek

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Gumulski, J., Jankowska, M., Spinczyk, D. (2022). Non-invasive Measurement of Human Pulse Based on Photographic Images of the Face. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2022. Advances in Intelligent Systems and Computing, vol 1429. Springer, Cham. https://doi.org/10.1007/978-3-031-09135-3_38

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