Abstract
This paper investigates fundamental mechanisms of brightness changes in heart rate (HR) measurement from face images through three kinds of experiments; (i) measurement of light reflection from cheek covered with/without copper film, (ii) spectroscopy measurement of reflection light from face and (iii) simultaneous measurement of face images and laser speckle images. The brightness change of the face skin are found to be caused by both the green light absorption variation by the blood volume changes and the light reflection variation by pulsatory face movements. The Real-time Pulse Extraction Method (RPEM), designed to extract the variation of light absorption by removing motion noise, is corroborated for the robustness by comparing the RPEM with the pulse wave of the ear photoplethysmography. The RPEM is also applied to heart rate measurements of seven participants during office work under non-controlled condition in order to evaluate continuous real-time HR monitoring. RMSE = 6.7 bpm is achieved as an average result of seven participants in five days with the 44% of HR measured rate with respect to the number of reference HRs from the electrocardiogram during face is detected. The result indicates that the RPEM method enables HR monitoring in daily life.
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References
Pantelopoulos, A., Bourbakis, N.G.: A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Trans. Syst., Man, Cybern. Part C Appl. Rev. 40(1), 1–12 (2010)
Inomata, A., Yaginuma, Y.: Hassle-free sensing technologies for monitoring daily health changes. Fujitsu Sci. Tech. J. 50(1), 78–83 (2014)
Uchida, D., Nakata, Y., Inomata, A., Shiotsu, S., Yaginuma, Y.: Hassle-free sensing technologies for human health monitoring. In: The IEICE General Conference/The Institute of Electronics, Information and Communication Engineers, S-16 (2015)
Reginatto, B., Taylor, K., Patterson, M., Caulfield, B.: Context aware falls risk assessment: a case study comparison. In: The Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 5477–5480 (2015)
Dyer, A.R., Persky, V., Stamler, J., Paul, O., Shekelle, R.B., Berkson, D.M., Lepper, M., Schoenberger, J.A., Lindberg, H.A.: Heart rate as a prognostic factor for coronary heart disease and mortality: findings in three Chicago epidemiologic studies. Am. J. Epidemio 112, 736–749 (1980)
Jensen, M.T., Suadicani, P., Hein, H.O., Gyntelberg, F.: Elevated resting heart rate, physical fitness and all-cause mortality: a 16-year follow-up in the Copenhagen Male Study. Heart 99(12), 882–887 (2013)
Broeders, J.H., Conchell, J.C.: Wearable electronic devices monitor vital signs, activity level, and more: health monitoring is going wearable. Analog Dialogue 41(12), 1–6 (2014)
Scalise, L.: Non contact heart monitoring. In: TechOpen, p. 84 (2012). www.intechopen.com
Yang, C., Cheung, G., Stankovic, V.: Estimating heart rate via depth video motion tracking. In: The Annual International Conference of the IEEE Multimedia and Expo (ICME), pp. 1–6 (2015)
Costa, D.: Optical remote sensing of heartbeats. Opt. Commun. 117(5–6), 395–398 (1995)
Parra, J.E., Costa, G.: Optical remote sensing of heartbeats. Proc. SPIE – Int. Soc. Opt. Eng. 4368, 113–121 (2001)
Tanaka, S., Matsumoto, Y., Wakimoto, K.: Unconstrained and non-invasive measurement of heart-beat and respiration periods using a phonocardiographic sensor. Med. Biol. Eng. Comput. 40, 246–252 (2001)
Takano, C., Ohta, Y.: Heart rate measurement based on a time-lapse image. Med. Eng. Phys. 29, 853–857 (2007)
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)
Poh, M.Z., McDuff, D.J., Picard, R.W.: Advancements in noncontact, multiparameter physiological measurements using a webcam. IEEE Trans. Biomed. Eng. 58(1), 7–11 (2011)
Kwon, S., Kim, H., Park, S.: Validation of heart rate extraction using video imaging on a built-in camera system of a smartphone. In: The Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 2174–2177 (2012)
Balakrishnan, G., Durand, F., Guttag, J.: Detecting pulse from head motions in video. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3430–3437 (2013)
Li, X., Chen, J., Zhao, G., Pietikainen, M.: Remote heart rate measurement from face videos under realistic situations. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4321–4328 (2014)
Sakata, M., Uchida, D., Inomata, A., Yaginuma, Y.: Continuous non-contact heart rate measurement using face imaging. In: The IEICE General Conference/The Institute of Electronics, Information and Communication Engineers, vol. 1, p. 73 (2013)
Steknke, J.M., Shephered, A.P.: Effects of temperature on optical absorbance spectra of oxy-, carboxy-, and deoxyhemoglobin. Clin. Chem. 38(7), 1360–1364 (1992)
Forrester, K.R., Tulip, J., Leonard, C., Stewart, C., Bray, R.C.: A laser speckle imaging technique for measuring tissue perfusion. IEEE Trans. Biomed. Eng. 51(11), 2074–2084 (2004)
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Uchida, D. et al. (2017). Continuous Real-Time Measurement Method for Heart Rate Monitoring Using Face Images. In: Fred, A., Gamboa, H. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2016. Communications in Computer and Information Science, vol 690. Springer, Cham. https://doi.org/10.1007/978-3-319-54717-6_13
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DOI: https://doi.org/10.1007/978-3-319-54717-6_13
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