Abstract
In this paper, we propose a novel noncontact pulse wave monitoring method that is robust to fluctuations in illumination through use of two-band infrared video signals. Because the proposed method uses infrared light for illumination, the method can be used to detect a pulse wave on a human face without visible lighting. The corresponding two-band pixel values in the video signals can be separated into hemoglobin and shading components by application of a separation matrix in logarithmic space for the two pixel values. Because the shading component has been separated, the extracted hemoglobin component is then robust to fluctuations in the illumination. The pixel values in the region of interest were spatially averaged over all the pixels of each frame. These averaged values were then used to form the raw trace signal. Finally, the pulse wave and the corresponding pulse rate were obtained from the raw trace signal through several signal processing stages, including detrending, use of an adaptive bandpass filter, and peak detection. We evaluated the absolute error rate for the pulse rate between the estimated value and the ground truth obtained using an electrocardiogram. In the experiments, we found that the performance of the proposed method was greatly improved compared with that of conventional methods using single-band infrared video.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Verkruysse W, Svaasand LO, Nelson JS (2008) Remote plethysmographic imaging using ambient light. Opt Exp 16(26):21434–21445
Poh MZ, McDuff DJ, Picard RW (2010) Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Opt Exp 18(10):10762–10774
Poh MZ, McDuff DJ, Picard RW (2011) Advancements in noncontact, multiparameter physiological measurements using a webcam. IEEE Trans Biomed Eng 58(1):7 11
McDuff D, Gontarek S, Picard RW (2014) Improvements in remote cardio-pulmonary measurement using a five band digital camera. IEEE Trans Biomed Eng 61(10):2593–2601
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 and imaging conference, vol 2015, Number 1, October 2015, pp 207–211
Garbey M, Sun N, Merla A, Pavlidis I (2007) Contact-free measurement of cardiac pulse based on the analysis of thermal imagery. IEEE Trans Biomed Eng 54(8):1418–1426
Zeng W, Zhang Q, Zhou Y, Xu G, Liang G (2015) Infrared video based non-invasive heart rate measurement. IEEE conference on robotics and biomimetics, December 6–9, 2015, pp 1041–1104
Hamedani K, Bahmani Z, Mohammadian A (2016) Spatio-temporal filtering of thermal video sequences for heart rate estimation. Expert Syst Appl 54:88–94
Van Gastel S, Stuijk, De Haan (2015) Motion robust remote-PPG in infrared. IEEE Trans Bioeng 62(5):1425–1433
Hulsbusch M (2008) An image-based functional method for opto-electronic detection of skin-perfusion (in German). Dissertation PhD, RWTH Aachen, Aachen, Germany
Corral LF, Paez G, Strojnik M (2011) Optimal wavelength selection for non-contact reflection photoplethysmography. 22nd Congress of the International Commission for Optics, Puebla, Mexico, Proc. SPIE, vol 8011, 15–19 Aug, pp 8011–8091
Tarvainen MP, Ranta-aho PO, Karjalainen PA (2002) An advanced detrending method with application to HRV analysis. Biomed Eng IEEE Trans 49(2):172–175
Acknowledgements
This work was supported in part by the MEXT/JST COI STREAM program.
Author information
Authors and Affiliations
Corresponding author
About this article
Cite this article
Mitsuhashi, R., Okada, G., Kurita, K. et al. Noncontact pulse wave detection by two-band infrared video-based measurement on face without visible lighting. Artif Life Robotics 23, 345–352 (2018). https://doi.org/10.1007/s10015-018-0430-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10015-018-0430-5