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Noncontact heart rate measurement using a high-sensitivity camera in a low-light environment

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Abstract

We propose a method for the remote estimation of the heart rate and heart rate variability spectrogram by analyzing the hemoglobin concentration obtained from RGB facial videos taken in a low-light environment. The monitoring of emotion has potential in areas such as market research, safety, and health. In particular, methods of analyzing the heart rate obtained from RGB video are expected to be used practically. However, these studies cannot be applied in dark locations where monitoring is necessary, such as an infant’s bedroom, a crime-prone road, and within a car. The proposed method, therefore, uses a highly sensitivity RGB camera capable of capturing videos at low illuminance. As the result, we could measure the heart rate with accuracy exceeding 99% and estimate the heart rate variability spectrogram with high accuracy for low-light environments of 10 lx, which corresponds to brightness levels of the monitoring environments given above.

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References

  1. Darwin C, Cummings MM, Duchenne GB (1872) The expression of the emotions in man and animals. John Murray, London

    Book  Google Scholar 

  2. Ekman P (1993) Facial expression and emotion. Am Psychol 48(4):384

    Article  Google Scholar 

  3. Zhang T, Johnson MH, Levinson SE (2004) Children’s Emotion Recognition in an Intelligent Tutoring Scenario. In: Proc. Eighth European Conf. Speech Comm. and Technology (INTERSPEECH)

  4. Kwon OW, Chan K, Hao L, Lee TW (2003) Emotion Recognition by Speech Signals. In: Proc. Eighth European Conf. Speech Comm. and Technology (EUROSPEECH)

  5. Park B-J, Jang E-H, Kim S-H, Huh C, Sohn J-H (2012) Seven emotion recognition by means of particle swarm optimization on physiological signals: Seven emotion recognition. In: Proc. 9th IEEE ICNSC, Apr. 2012, pp. 277–282

  6. Kurita K, Yonezawa T, Kuroshima M, Tsumura N (2015) Non-contact video based estimation for heart rate variability spectrogram using ambient light by extracting hemoglobin information. Color Imag Conf 2015(1):207–211

    Google Scholar 

  7. Okada G, Yonezawa T, Kurita K, Tsumura N (2018) Monitoring emotion by remote measurement of physiological signals using an RGB camera. ITE Trans Media Technol Appl 6(1):131–137

    Article  Google Scholar 

  8. Alaoui-Ismaili O, Robin O, Rada H, Dittmar A, Vernet-Maury E (1997) Basic emotions evoked by odorants: Comparison between autonomic responses and self-evaluation. Physiol Behav 62:713–720

    Article  Google Scholar 

  9. Zhao F, Li M, Qian Y, Tsien JZ (2013) Remote measurements of heart and respiration rates for telemedicine. PLoS One 8(10):e71384

    Article  Google Scholar 

  10. Ojima N, Minami T, Kawai M (1997) Transmittance measurement of cosmetic layer applied on skin using processing. In: Proceeding of The 3rd Scientific Conference of the Asian Societies of Cosmetic Scientists

  11. Viola P, Jones M (2001) 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, Volume: 1, pp. 511–518

  12. Tarvainen MP, Ranta-aho PO, Karjalainen PA (2002) An advanced detrending method with application to HRV analysis. IEEE T Bio-med Eng 49(2):172–175

    Article  Google Scholar 

  13. Vila J, Palacios F, Presedo J, Ferna ́ndez-Delgado M, Felix P, Barro S (1997) Time-frequency analysis of heart-rate variability. IEEE Eng Med Biol Mag 16(5):119–126

    Article  Google Scholar 

  14. Berntson GG, Thomas Bigger J, Eckberg DL, Grossman P, Kaufmann PG, Malik M, Nagaraja HN, Porges SW, Saul JP, Stone PH, Van Der Molen MW (1997) Heart rate variability: Origins, methods, and interpretive caveats. Psychophysiology 34:623–648

    Article  Google Scholar 

  15. Press WH, Teukolsky SA, Vetterling WA, Flannery BP (2001) Numerical recipes in Fortran 77: the art of scientific computing, vol 1, 2nd edn. Cambridge University Press, New York

    MATH  Google Scholar 

  16. Welch PD (1967) The use of fast fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms”. IEEE Trans Audio Electroacoust AU 15(2):70–73

    Article  Google Scholar 

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Correspondence to Genki Okada.

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Okada, G., Mitsuhashi, R., Kagawa, K. et al. Noncontact heart rate measurement using a high-sensitivity camera in a low-light environment. Artif Life Robotics 24, 6–11 (2019). https://doi.org/10.1007/s10015-018-0461-y

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  • DOI: https://doi.org/10.1007/s10015-018-0461-y

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