For citation:
Volkov I. Y., Sagaidachnyi A. A., Fomin A. V. Photoplethysmographic imaging of hemodynamics and two-dimensional oximetry. Izvestiya of Saratov University. Physics , 2022, vol. 22, iss. 1, pp. 15-45. DOI: 10.18500/1817-3020-2022-22-1-15-45, EDN: VVFVKY
Photoplethysmographic imaging of hemodynamics and two-dimensional oximetry
Background and Objectives: A review of recent papers devoted to actively developing methods of photoplethysmographic imaging (PPGI) of blood volume pulsations in vessels and non-contact two-dimensional oximetry on the surface of the human body is carried out. Results: The physical fundamentals and technical aspects of PPGI and oximetry have been considered. The diversity of physiological parameters available for analysis by PPGI has been shown. The prospects of PPGI technology have been discussed. The possibilities of non-contact determination of blood oxygen saturation SpO2 (saturation of pulse O2) have been described. The relevance of remote determination of the level of oxygenation due to the spread of a new coronavirus infection SARS-CoV-2 (COVID-19) has been emphasized. Most of the works under consideration cover the period of 2010–2021 years.
- Strokanev K. S. Review and Classification of Current Methods for Remote Photoplethysmography of the Face. Intellektual’nye sistemy v proizvodstve [Intelligent Systems in Manufacturing], 2021, vol. 19, no. 2, pp. 129–138 (in Russian). https://www.doi.org/10.22213/2410-9304-2021-2-129-138
- Hertzman A. B. The blood supply of various skin areas as estimated by the photoelectric plethysmograph. Am. J. Physiol., 1938, vol. 124, no. 2, pp. 328–340. https://www.doi.org/10.1152/ajplegacy.1938.124.2.328
- De Trafford J., Lafferty K. What does photoplethysmography measure? Medical & Biological Engineering & Computing, 1984, vol. 22, no. 5, pp. 479–480. https://www.doi.org/10.1007/BF02447713
- Sun Y. Photoplethysmography revisited : From contact to noncontact, from point to imaging. IEEE Transactions on Biomedical Engineering, 2015, vol. 63, no. 3, pp. 463–477. https://www.doi.org/10.1109/TBME.2015.2476337
- Aoyagi T., Kishi M., Yamaguchi K., Watanabe S. Improvement of the earpiece oximeter. Japanese Society of Medical Electronics and Biological Engineering, 1974, vol. 974, pp. 90–91.
- Tremper K. K., Barker S. J. Pulse oximetry. Anesthesiology, 1989, vol. 70, no. 1, pp. 98–108. https://www.doi.org/10.1097/00000542-198901000-00019
- Blazek V., Rutten W., Such O. A method for spaceresolved, noncontacting and functional visualization of dermal perfusion. German patent, no. P196 38 873.2, 1996.
- Wu T., Blazek V., Schmitt H. J. Photoplethysmography imaging : A new noninvasive and non-contact method for mapping of the dermal perfusion changes. Proc. SPIE, 2000, no. 4163, pp. 62–70. https://www.doi.org/10.1117/12.407646
- Takano C., Ohta Y. Heart rate measurement based on a time-lapse image. Med. Eng. Phys., 2007, vol. 29, no. 8, pp. 853–857. https://www.doi.org/10.1016/j.medengphy.2006.09.006
- Verkruysse W., Svaasand L., Nelson J. Remote plethysmographic imaging using ambient light. Optics Express, 2008, vol. 16, no. 26, pp. 21434–21445. https://www.doi.org/10.1364/oe.16.021434
- Kamshilin A. A., Miridonov S., Teplov V., Saarenheimo R., Nippolainen E. Photoplethysmographic imaging of high spatial resolution. Biomedical Optics Express, 2011, vol. 2, no. 4, pp. 996–1006. https://www.doi.org/10.1364/BOE.2.000996
- Zaproudina N., Teplov V., Nippolainen E., Lipponen J. A., Kamshilin A. A., Närhi M., Giniatullin R. Asynchronicity of facial blood perfusion in migraine. PloS ONE, 2013, vol. 8, no. 12, e80189. https://www.doi.org/10.1371/journal.pone.0080189
- Wieringa F., Mastik F., van der Steen A. Contactless multiple wavelength photoplethysmographic imaging : A first step toward «SpO2 camera» technology. Ann. Biomed. Eng., 2005, vol. 33, no. 8, pp. 1034–1041. https://www.doi.org/10.1007/s10439-005-5763-2
- Wieringa F., Mastik F. In Vitro Demonstration of an SpO2-Camera. Computers in Cardiology, 2007, no. 34, pp. 749–751.
- Simonyan M. A., Posnenkova O. M., Kiselev A. R. Capabilities of photoplethysmography as a method for screening of cardiovascular system pathology. Cardio-IT, 2020, vol. 7, no. 1, pp. 102 (in Russian). https://www.doi.org/10.15275/cardioit.2020.0102
- Semchuk I. P., Zmievskoi G. N., Muravskaia N. P., Samorodov A. V. Non-contact photoplethysmograph for the study of vital body functions. Pribory [Instruments], 2018, vol. 217, no. 7, pp. 1–6 (in Russian).
- Akishin A. D., Semchuk I. P., Nikolaev A. P. Development of a device for control of the state of the organism based on photopletismography using technologies of digital adaptive filtration. System Analysis and Management in Biomedical Systems, 2020, vol. 19, no. 4, pp. 100–107 (in Russian). https://www.doi.org/10.36622/VSTU.2020.19.4.0124
- Avanesov A. A., Kopeliovich M. V., Kalinin K. B., Shcherban I. V. Approaches to evaluating the frequency of heart reductions by video recording analysis. Trudy Severo-Kavkazskogo filiala Moskovskogo tekhnicheskogo universiteta sviazi i informatiki [Proceedings of the North Caucasian branch of the Moscow Technical University of Communications and Informatics], 2020, no. 1, pp. 27–40 (in Russian).
- Semchuk I. P., Zmievskoy G. N., Muravskaya N. P., Volkov A. K., Murashko M. A., Samorodov A. V. An experimental study of contactless photoplethysmography techniques. Meditsinskaya tekhnika [Biomedical Engineering], 2019, no. 1, pp. 1–4 (in Russian).
- Kamshilin A. A., Sidorov I. S., Babayan L., Volynsky M. A., Giniatullin R., Mamontov O. V. Accurate measurement of the pulse wave delay with imaging photoplethysmography. Biomedical Optics Express, 2016, vol. 7, no. 12, pp. 5138–5147. https://www.doi.org/10.1364/BOE.7.005138
- Kamshilin A. A., Krasnikova T. V., Volynsky M. A., Miridonov S. V., Mamontov O. V. Alterations of blood pulsations parameters in carotid basin due to body position change. Scientific Reports, 2018, vol. 8, no. 1, pp. 1–9. https://www.doi.org/10.1038/s41598-018-32036-7
- Chatterjee S., Phillips J. P., Kyriacou P. A. Monte carlo investigation of the effect of blood volume and oxygen saturation on optical path in reflectance pulse oximetry. Biomedical Physics & Engineering Express, 2016, vol. 2, no. 6, e065018. https://www.doi.org/10.1088/2057-1976/2/6/065018
- Budidha K., Kyriacou P. A., Abay T. Y. Optical techniques for blood and tissue oxygenation. Ref. Modul. Biomed. Sci., 2019, vol. 3, pp. 461–472. https://www.doi.org/10.1016/B978-0-12-801238-3.10886-4
- Allen J. Photoplethysmography and its application in clinical physiological measurement. Physiological Measurement, 2007, vol. 28, no. 3, pp. R1–39. https://www.doi.org/10.1088/0967-3334/28/3/R01
- Gastel M., Stuijk S., Haan G. Camera-based pulseoximetry – validated risks and opportunities from theoretical analysis. Biomedical Optics Express, 2018, vol. 9, no. 1, pp. 102–119. https://www.doi.org/10.1364/BOE.9.000102
- Gastel M., Stuijk S., Haan G. New principle for measuring arterial blood oxygenation, enabling motion-robust remote monitoring. Scientific Reports, 2016, vol. 6, no. 1, e38609. https://www.doi.org/10.1038/srep38609
- Nitzan M., Adar Y. Comparison of systolic blood pressure values obtained by photoplethysmography and by korotkoff sounds. Sensors, 2013, vol. 13, no. 11, pp. 14797–14812. https://www.doi.org/10.3390/s131114797
- Aoyagi T. Pulse oximetry : Its invention, theory, and future. Journal of Anesthesia, 2003, vol. 17, no. 4, pp. 259–266. https://www.doi.org/10.1007/s00540-003-0192-6
- Lapitan D. G., Tarasov A. P. Analytical assessment of the modulation depth of photoplethysmographic signal based on the modified Beer-Lambert law. 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL), 2019, pp. 103–106. https://www.doi.org/10.1109/CAOL46282.2019.9019552
- Moço A. V., Stuijk S., de Haan G. Skin inhomogeneity as a source of error in remote PPG-imaging. Biomedical Optics Express, 2016, vol. 7, no. 11, pp. 4718–4733. https://www.doi.org/10.1364/BOE.7.004718
- Fine I. The optical origin of the PPG signal. Saratov Fall Meeting 2013 : Optical Technologies in Biophysics and Medicine XV. 2014, no. 9031, e903103. https://www.doi.org/10.1117/12.2051228
- Kamshilin A. A., Nippolainen E., Sidorov I. S., Vasilev P. V., Erofeev N. P., Podolian N. P., Romashko R. V. A new look at the essence of the imaging photoplethysmography. Scientific Reports, 2015, vol. 5, no. 1, pp. 10494. https://www.doi.org/10.1038/srep10494
- Moço A. V., Stuijk S., de Haan, G. Motion robust PPG-imaging through color channel mapping. Biomedical Optics Express, 2016, vol. 7, no. 5, pp. 1737–1754. https://www.doi.org/10.1364/BOE.7.001737
- Sidorov I. S., Romashko R. V., Koval V. T., Giniatullin R., Kamshilin A. A. Origin of infrared light modulation in reflectance mode photoplethysmography. PLoS ONE, 2016, vol. 11, no. 10, e0165413. https://www.doi.org/10.1371/journal.pone.0165413
- Farrell T. J., Patterson M. S., Wilson B. A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo. Medical Physics, 1992, vol. 19, no. 4, pp. 879–888. https://www.doi.org/10.1118/1.596777
- Rogatkin D. A. Physical foundations of optical oximetry. Meditsinskaya fizika [Medical Physics], 2012, vol. 2, no. 54, pp. 97–113 (in Russian).
- Marcinkevics Z., Rubins U. Imaging photoplethysmography for clinical assessment of cutaneous microcirculation at two different depths. Journal of Biomedical Optics, 2016, vol. 21, no. 3, e35005. https://www.doi.org/10.1117/1.JBO.21.3.035005
- Verkruysse W., Bartula M. Calibration of contactless pulse oximetry. Anesthesia and Analgesia, 2017, vol. 124, no. 1, pp. 136–145. https://www.doi.org/10.1213/ANE.0000000000001381
- Rubins U., Erts R., Nikiforovs V. The blood perfusion mapping in the human skin by photoplethysmography imaging. IFMBE Proceedings, 2010, vol. 29, pp. 304–306. https://www.doi.org/10.1007/978-3-642-13039-7_76
- Sun Y., Hu S., Azorin-Peris V. Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise. Journal of Biomedical Optics, 2011, vol. 16, no. 7, e077010. https://www.doi.org/10.1117/1.3602852
- Zheng J., Hu S., Azorin-Peris V. Remote simultaneous dual wavelength imaging photoplethysmography : A further step towards 3-D mapping of skin blood microcirculation. Proc. of SPIE, 2008, vol. 6850, e68500S. https://www.doi.org/10.1117/12.761705
- Trumpp A., Bauer P. L. The value of polarization in camera-based photoplethysmography. Biomedical Optics Express, 2017, vol. 8, no. 6, pp. 2822–2834. https://www.doi.org/10.1364/BOE.8.002822
- Bousefsaf F., Maaoui C., Pruski A. Continuous wavelet filtering on webcam photoplethysmographic signals to remotely assess the instantaneous heart rate. Biomedical Signal Processing and Control, 2013, vol. 8, no. 6, pp. 568–574. https://www.doi.org/10.1016/j.bspc.~2013.05.010
- Taranov A. A., Spiridonov I. N. Non-contact measurement of arterial pulse rate. Biotekhnosfera [Biotechnosfera], 2014, vol. 3, no. 33, pp. 43–45 (in Russian).
- Sun Y., Papin C., Azorin-Peris V., Kalawsky R., Greenwald S., Hu S. Use of ambient light in remote photoplethysmographic systems : Comparison between a high-performance camera and a lowcost webcam. Journal of Biomedical Optics, 2012, vol. 17, no. 3, e037005. https://www.doi.org/10.1117/1.JBO.17.3.037005
- Mironenko Y., Kalinin K., Kopeliovich M., Petrushan M. Remote photoplethysmography : Rarely considered factors. Proceedings of the IEEE / CVF Conference on Computer Vision and Pattern Recognition Workshops, 2020, pp. 296–297.
- Humphreys K., Ward T., Markham C. A CMOS Camera-Based Pulse Oximetry Imaging System. 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, no. 2005, pp. 3494–3497. https://www.doi.org/10.1109/IEMBS.2005.1617232
- Hsu Y., Lin Y.-L., Hsu W. Learning-based heart rate detection from remote photoplethysmography features. 2014 IEEE Int. Conf. Acoust. Speech Signal Process, 2014, pp. 4433–4437. https://www.doi.org/10.1109/ICASSP.~2014.6854440
- Poh M.-Z., McDuff D. J., Picard R. W. Advancements in noncontact, multiparameter physiological measurements using a webcam. IEEE Transactions on Biomedical Engineering, 2011, vol. 58, no. 1, pp. 7–11. https://www.doi.org/10.1109/TBME.2010.2086456
- Fallet S., Moser V. Imaging Photoplethysmography : What are the Best Locations on the Face to Estimate Heart Rate, Computing in Cardiology, 2016, vol. 43, pp. 341–344. https://www.doi.org/10.22489/Cinc.~2016.098-236
- Kumar M., Veeraraghavan A. Contact-free camera measurements of vital signs. SPIE, 2015, pp. 1–4. https://www.doi.org/10.1117/2.1201511.006184
- Shao D., Liu C., Tsow F., Yang Y., Du Z., Iriya R., Yu H., Tao N. Noncontact monitoring of blood oxygen saturation using camera and dual-wavelength imaging system. IEEE Transactions on Biomedical Engineering, 2016, vol. 63, no. 6, pp. 1091–1098. https://www.doi.org/10.1109/TBME.2015.2481896
- Feng L., Po L. M., Xu X., Li Y., Ma R. Motion-resistant remote imaging photoplethysmography based on the optical properties of skin. IEEE Transactions on Circuits and Systems for Video Technology, 2015, vol. 25, no. 5, pp. 879–891. https://www.doi.org/10.1109/TCSVT.2014.2364415
- Zou J., Chen T., Yang X. Non-Contact Real-Time Heart Rate Measurement Algorithm Based on PPG-Standard Deviation. Computers, Materials & Continua, 2019, vol. 60, no. 3, pp. 1029–1040. https://www.doi.org/10.32604/cmc.~2019.05793
- Trumpp A., Schell J. Vasomotor assessment by camera-based photoplethysmography. Current Directions in Biomedical Engineering, 2016, vol. 2, no. 1, pp. 199–202. https://www.doi.org/10.1515/cdbme-2016-0045
- Poh M.-Z., McDuff D. J., Picard R. W. Non-contact, automated cardiac pulse measurements using video imaging and blind source separation. Optics Express, 2010, vol. 18, no. 10, pp. 10762–10774. https://www.doi.org/10.1364/OE.18.010762
- Tulyakov S., Alameda-Pineda X., Ricci E., Yin L., Cohn J. F., Sebe N. Self-Adaptive Matrix Completion for Heart Rate Estimation from Face Videos under Realistic Conditions. Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 2396–2404.
- Bousefsaf F., Maaoui C., Pruski A. Automatic selection of webcam photoplethysmographic pixels based on lightness criteria. J. Med. Biol. Eng., 2017, vol. 37, no. 3, pp. 374–385. https://www.doi.org/10.1007/s40846-017-0229-1
- Bousefsaf F., Maaoui C., Pruski A. Continuous wavelet filtering on webcam photoplethysmographic signals to remotely assess the instantaneous heart rate. Biomed. Signal Process. Control, 2013, vol. 8, no. 6, pp. 568–574. https://www.doi.org/10.1016/j.bspc.2013.05.010
- Bobbia S., Macwan R., Benezeth Y., Mansouri A., Dubois J. Unsupervised skin tissue segmentation for remote photoplethysmography. Pattern Recognit Lett., 2017, vol. 124, no. 9, pp. 1–9. https://www.doi.org/10.1016/j.patrec.2017.10.017
- Bobbia S., Luguern D., Benezeth Y., Nakamura K., Gomez R., Dubois J. Real-Time Temporal Superpixels for Unsupervised Remote Photoplethysmography. Proceedings of the IEEE / CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018, pp. 1341–1348. https://www.doi.org/10.1109/CVPRW.2018.00182
- Bobbia S., Benezeth Y., Dubois J. Remote photoplethysmography based on implicit living skin tissue segmentation. Proc. of the 23rd International Conference on Pattern Recognition (ICPR), 2016, pp. 361–365.
- Wang W., Stuijk S., de Haan G. Living-skin classification via remote-ppg. IEEE Transactions on Biomedical Engineering, 2017, vol. 64, no. 12, pp. 2781–2792. https://www.doi.org/10.1109/TBME.2017.2676160
- Tarassenko L., Villarroel M., Guazzi A., Jorge J., Clifton D., Pugh C. Non-contact video-based vital sign monitoring using ambient light and auto-regressive models. Physiological Measurement, 2014, vol. 35, no. 5, pp. 807–831. https://www.doi.org/10.1088/0967-3334/35/5/807
- Chwyl B., Chung A. G., Amelard R., Deglint J., Clausi D. A., Wong A. SAPPHIRE : Stochastically ac[1]quired photoplethysmogram for heart rate inference in realistic environments. Proc. of the IEEE International Conference on Image Processing (ICIP), 2016, no. 2016, pp. 1230–1234. https://www.doi.org/10.1109/ICIP.~2016.7532554
- Chaichulee S., Villarroel M., Jorge J., Arteta C., Green G., McCormick K., Zisserman A., Tarassenko L. Multi-Task Convolutional Neural Network for Patient Detection and Skin Segmentation in Continuous Non-Contact Vital Sign Monitoring. Proc. of the 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), 2017, pp. 266–272. https://www.doi.org/10.1109/FG.2017.41
- Hu S., Peris V., Echiadis A., Zheng J., Shi P. Development of effective photoplethysmographic measurement techniques : From contact to non-contact and from point to imaging. 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009, pp. 6550–6553. https://www.doi.org/10.1109/IEMBS.2009.5334505
- Villarroel M., Guazzi A. Continuous non-contact vital sign monitoring in neonatal intensive care unit. Healthcare Technology Letters, 2014, vol. 1, no. 3, pp. 87–91. https://www.doi.org/10.1049/htl.2014.0077
- Wang W., Brinker A. C. D., Stuijk S., Haan G. D. Algorithmic principles of remote PPG. IEEE Trans. Biomed. Eng., 2017, vol. 64, no. 7, pp. 1479–1491. https://www.doi.org/10.1109/TBME.2016.2609282
- Li X., Chen J., Zhao G., Pietikainen M. Remote heart rate measurement from face videos under realistic situations. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014, pp. 4264–4271. https://www.doi.org/10.1109/CVPR.2014.543
- Strokanev K. S., Korobeynikov A. V. System of photoplethysmography by face video image with applying the euler magnification. Intellektual’nye sistemy v proizvodstve [Intelligent Systems in Manufacturing], 2016, vol. 3, no. 30, pp. 56–59 (in Russian).
- Wu H.-Y., Rubinstein M., Shih E., Guttag J. V., Durand F., Freeman W. T. Eulerian video magnification for revealing subtle changes in the world. ACM Trans. Graph, 2012, vol. 31, no. 4, pp. 65. https://www.doi.org/10.1145/2185520.2185561
- Lewandowska M., Ruminski J., Kocejko T., Nowak J. Measuring pulse rate with a webcam – a non-contact method for evaluating cardiac activity. 2011 Federated Conference on Computer Science and Information Systems (FedCSIS), 2011, pp. 405–410.
- De Haan G., Jeanne V. Robust pulse rate from chrominance-based rppg. IEEE Transactions on Biomedical Engineering, 2013, vol. 60, no. 10, pp. 2878–2886. https://www.doi.org/10.1109/TBME.2013.2266196
- De Haan G., Van Leest A. Improved motion robustness of remote-PPG by using the blood volume pulse signature. Physiological Measurement, 2014, vol. 35, no. 9, pp. 1913–1926. https://www.doi.org/10.1088/0967-3334/35/9/1913
- Wang W., Stuijk S., De Haan G. A Novel Algorithm for Remote Photoplethysmography : Spatial Subspace Rotation. IEEE Transactions on Biomedical Engineering, 2016, vol. 63, no. 9, pp. 1974–1984. https://www.doi.org/10.1109/TBME.2015.2508602
- Hsu G., Ambikapathi A., Chen M. Deep learning with time-frequency representation for pulse estimation from facial videos. IEEE International Joint Conference on Biometrics (IJCB), 2017, pp. 383–389. https://www.doi.org/10.1109/BTAS.2017.8272721
- Chen W., McDuff D. DeepPhys : Videobased physiological measurement using convolutional attention networks. European Conference on Computer Vision (ECCV), 2018, pp. 356–373.
- Niu X., Shan S., Han H., Chen X. RhythmNet : End-to-end heart rate estimation from face via spatial-temporal representation. IEEE Transactions on Image Processing, 2020, no. 29, pp. 2409–2423. https://www.doi.org/10.1109/TIP.~2019.2947204
- Yu Z., Li X., Zhao G. Remote photoplethysmography signal measurement from facial videos using spatio-temporal networks. Proceedings of the British Machine Vision Conference (BMVC), 2019, pp. 1–12.
- Heusch G., Marcel S. Pulse-based features for face presentation attack detection. IEEE International Conference on Biometrics Theory, Applications and Systems (BTAS), 2018, pp. 1–8. https://www.doi.org/10.1109/BTAS.2018.8698579
- Liu S.-Q., Lan X., Yuen P. Remote photoplethysmography correspondence feature for 3d mask face presentation attack detection. European Conference on Computer Vision (ECCV), 2018, pp. 577–594. https://www.doi.org/10.1007/978-3-030-01270-0_34
- Speth J., Vance N., Flynn P., Bowyer K., Czajka A. Remote Pulse Estimation in the Presence of Face Masks. 2021. ArXiv preprint arXiv:2101.04096.
- Mannapperuma K., Holton B. D. Performance limits of ICA-based heart rate identification techniques in imaging photoplethysmography. Physiological Measurement, 2015, vol. 36, no. 1, pp. 67–83. https://www.doi.org/10.1088/0967-3334/36/1/67
- Forrester K. R., Tulip J., Leonard C., Stewart C., Bray R. C. A laser speckle imaging technique for measuring tissue perfusion. IEEE Transactions on Biomedical Engineering, 2004, vol. 51, no. 11, pp. 2074–2084. https://www.doi.org/10.1109/TBME.2004.834259
- Serov A., Steinacher B., Lasser T. Full-field laser Doppler perfusion imaging and monitoring with an intelligent CMOS camera. Optics Express, 2005, vol. 13, no. 10, pp. 3681–3689. https://www.doi.org/10.1364/opex.13.003681
- Kamshilin A. A., Teplov V., Nippolainen E., Miridonov S., Giniatullin R. Variability of microcirculation detected by blood pulsation imaging. PloS ONE, 2013, vol. 8, no. 2, e57117. https://www.doi.org/10.1371/journal.pone.0057117
- Iakovlev D., Dwyer V., Hu S., Silberschmidt V. Noncontact blood perfusion mapping in clinical applications. Biophotonics : Photonic Solutions for Better Health Care V, 2016, vol. 9887, pp. 55–56. https://www.doi.org/10.1117/12.2225216
- Aarts L. A., Jeanne V., Cleary J. P., Lieber C., Nelson J. S., Oetomo S. B., Verkruysse W. Non-contact heart rate monitoring utilizing camera photoplethysmography in the neonatal intensive care unit – a pilot study. Early Hum. Dev., 2013, vol. 89, no. 12, pp. 943–948. https://www.doi.org/10.1016/j.earlhumdev.2013.09.016
- Kumar M., Suliburk J. PulseCam : High-resolution blood perfusion imaging using a camera and a pulse oximeter. 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 2016, pp. 3904–3909. https://www.doi.org/10.1109/EMBC.2016.7591581
- Kumar M., Suliburk J. PulseCam : A camera-based, motion-robust and highly sensitive blood perfusion imaging modality. Scientific Reports, 2020, vol. 10, no. 1, pp. 1–17 https://www.doi.org/10.1038/s41598-020-61576-0
- Mamontov O. V., Krasnikova T. V., Volynsky M. A., Anokhina N. A., Shlyakhto E. V., Kamshilin A. A. Novel instrumental markers of proximal scleroderma provided by imaging photoplethysmography. Physiological Measurement, 2020, vol. 41, no. 4, e044004. https://www.doi.org/10.1088/1361-6579/ab807c
- Volynsky M. A., Margaryants N. B., Kamshilin A. A. Monitoring Changes in Capillary Blood Flow due to Thermal Impact Using Imaging Photoplethysmography. Imaging and Applied Optics, 2019, paper ITh3B.4. https://www.doi.org/10.1364/ISA.2019.ITh3B.4
- Kamshilin A. A., Lyubashina O. A. Assessment of Pain-Induced Changes in Cerebral Microcirculation by Imaging Photoplethysmography. International Work-Conference on Bioinformatics and Biomedical Engineering. Cham, Springer, 2019, pp. 479–489. https://www.doi.org/10.1007/978-3-030-17935-9_43
- Mamontov O. V., Shcherbinin A. V. Intraoperative Imaging of Cortical Blood Flow by Camera-Based Photoplethysmography at Green Light. Applied Sciences, 2020, vol. 10, no. 18, e6192. https://www.doi.org/10.3390/app10186192
- Kamshilin A. A., Volynsky M. A. Novel capsaicininduced parameters of microcirculation in migraine patients revealed by imaging photoplethysmography. The Journal of Headache and Pain, 2018, vol. 19, no. 1, pp. 43. https://www.doi.org/10.1186/s10194-018-0872-0
- Volynsky M. A., Mamontov O. V. Pulse wave transit time measured by imaging photoplethysmography in upper extremities. Journal of Physics : Conference Series, 2016, vol. 737, e012053. https://www.doi.org/10.1088/1742-6596/737/1/012053
- Nirala N., Periyasamy R., Kumar A. Study of skin flow motion pattern using photoplethysmogram. International Journal of Advanced Intelligence Paradigms, 2020, vol. 16, no. 3–4, pp. 241–264. https://www.doi.org/10.1504/IJAIP.~2020.10018682
- Blanik N., Blazek C., Pereira C., Blazek V., Leonhardt S. Frequency-selective quantification of skin perfusion behavior during allergic testing using photoplethysmography imaging. Medical Imaging 2014 : Image Processing, 2014, vol. 9034, e903429. https://www.doi.org/10.1117/12.2043567
- Allen J., Chen F. Low-frequency variability in photoplethysmography and autonomic function assessment. In: Photoplethysmography. Academic Press, 2022, pp. 277–318. https://www.doi.org/10.1016/B978-0-12-823374-0.00008-6
- Nishidate I., Hoshi A., Aoki Y., Nakano K., Niizeki K., Aizu Y. Noncontact imaging of plethysmographic pulsation and spontaneous low-frequency oscillation in skin perfusion with a digital red-green-blue camera. Dynamics and Fluctuations in Biomedical Photonics XIII, 2016, vol. 9707, e97070L. https://www.doi.org/10.1117/12.2212558
- Nishidate I., Tanabe C., McDuff D. J., Nakano K., Niizeki K., Aizu Y., Haneishi H. RGB camera-based noncontact imaging of plethysmogram and spontaneous low-frequency oscillation in skin perfusion before and during psychological stress. Proc. SPIE. Optical Diagnostics and Sensing XIX : Toward Point-of-Care Diagnostics, 2019, vol. 10885, pp. 9–16. https://www.doi.org/10.1117/12.2509752
- McDuff D., Nishidate I., Nakano K., Haneishi H., Aoki Y., Tanabe C., Aizu Y. Non-contact imaging of peripheral hemodynamics during cognitive and psychological stressors. Scientific Reports, 2020, vol. 10, no. 1, pp. 1–13. https://www.doi.org/10.1038/s41598-020-67647-6
- Khanoka B., Slovik Y., Landau D., Nitzan M. Sympathetically induced spontaneous fluctuations of the photoplethysmographic signal. Medical and Biological Engineering and Computing, 2004, vol. 42, no. 1, pp. 80–85. https://www.doi.org/10.1007/BF02351014
- Kublanov V. S., Purtov K. S. Heart rate variability study by remote photoplethysmography. Biomedical Radioelectronics, 2015, no. 8, pp. 3–9 (in Russian).
- Kublanov V. S., Purtov K. S. Researching the possibilities of remote photoplethysmography application to analysis of time-frequency changes of human heart rate variability. 2015 International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON), 2015, pp. 87–92. https://www.doi.org/10.1109/SIBIRCON.2015.7361857
- Kulminskiy D. D., Kurbako A. V., Skazkina V. V., Prokhorov M. D., Ponomarenko V. I., Kiselev A. R., Bezruchko B. P., Karavaev A. S. Development of a digital finger photoplethysmogram sensor. Izvestiya of Saratov University. Physics, 2021, vol. 21, iss. 1, pp. 58–68 (in Russian). https://www.doi.org/10.18500/1817-3020-2021-21-1-58-68
- Simonyan M. A., Skazkina V. V., Posnenkova O. M., Ishbulatov Yu. M, Shvartz V. A., Borovkova E. I., Gorshkov A. Yu., Fedorovich A. A., Dzhioeva O. N., Karavaev A. S., Gridnev V. I., Drapkina O. M., Kiselev A. R. Analysis of the spectral indices of the photoplethysmographic signals and their age-related dynamics for the task of screening of cardiovascular diseases. Profilakticheskaya meditsina [The Russian Journal of Preventive Medicine], 2021, vol. 24, no. 8, pp. 73–79 (in Russian). https://www.doi.org/10.17116/profmed20212408173
- Karavaev A. S., Borovik A. S., Borovkova E. I., Orlova E. A., Simonyan M. A., Ponomarenko V. I., Kiselev A. R. Low-frequency component of photoplethysmogram reflects the autonomic control of blood pressure. Biophysical Journal, 2021, vol. 120, no. 13, pp. 2657–2664. https://www.doi.org/10.1016/j.bpj.2021.05.020
- Kiselev A. R., Borovkova E. I., Shvartz V. A., Skazkina V. V., Karavaev A. S., Prokhorov M. D., Bockeria O. L. Low-frequency variability in photoplethysmographic waveform and heart rate during on-pump cardiac surgery with or without cardioplegia. Scientific Reports, 2020, vol. 10, no. 1, pp. 1–9. https://www.doi.org/10.1038/s41598-020-58196-z
- Tankanag A. V., Grinevich A. A., Tikhonova I. V., Chemeris N. K. An analysis of phase relationships between oscillatory processes in the human cardiovascular system. Biophysics, 2020, vol. 65, no. 1, pp. 159–164. https://www.doi.org/10.1134/s0006350920010194
- Tikhonova I. V., Grinevich A. A., Tankanag A. V. Analysis of phase interactions between heart rate variability, respiration and peripheral microhemodynamics oscillations of upper and lower extremities in human. Biomedical Signal Processing and Control, 2022, vol. 71, e103091. https://www.doi.org/10.1016/j.bspc.2021.103091
- Tankanag A., Krasnikov G., Mizeva I. A pilot study : Wavelet cross-correlation of cardiovascular oscillations under controlled respiration in humans. Microvascular Research, 2020, vol. 130, e103993. https://www.doi.org/10.1016/j.mvr.2020.103993
- Tankanag A. V., Krasnikov G. V., Chemeris N. K. Phase Coherence of Finger Skin Blood Flow Oscillations Induced by Controlled Breathing in Humans. Physics of Biological Oscillators : New Insights into Non-Equilibrium and Non-Autonomous Systems. Cham, Springer, 2021, pp. 281. https://www.doi.org/10.1007/978-3-030-59805-1_18
- Sagaidachnyi A. A., Skripal An. V., Fomin A. V., Usanov D. A. Determination of the amplitude and phase relationships between oscillations in skin temperature and photoplethysmography-measured blood flow in fingertips. Physiological Measurement, vol. 35, no. 2, pp. 153–166. https://www.doi.org/10.1088/0967-3334/35/2/153
- Sagaidachnyi A. A., Fomin A. V., Usanov D. A., Skripal An. V. Thermography-based blood flow imaging in human skin of the hands and feet : A spectral filtering approach. Physiological Measurement, 2017, vol. 38, no. 2, pp. 272–288. https://www.doi.org/10.1088/1361-6579/aa4eaf
- Sagaidachnyi A. A., Fomin A. V., Usanov D. A., Skripal An. V. Real-time technique for conversion of skin temperature into skin blood flow : Human skin as a low-pass filter for thermal waves. Computer Methods in Biomechanics and Biomedical Engineering, 2019, vol. 22, no. 12, pp. 1009–1019. https://www.doi.org/10.1080/10255842.2019.1615058
- Allan D., Chockalingam N., Naemi R. Validation of a non-invasive imaging photoplethysmography device to assess plantar skin perfusion, a comparison with laser speckle contrast analysis. Journal of Medical Engineering & Technology, 2021, vol. 45, no. 3, pp. 170–176. https://www.doi.org/10.1080/03091902.2021.1891309
- Volkov I. Yu., Fomin A. V., Mayskov D. I., Zaletov I. S., Skripal An. V., Sagaidachnyi A. A. Possibilities of photoplethysmographic visualization of peripheral hemodynamics in the low-frequency range. Metody komp’iuternoi diagnostiki v biologii i meditsine – 2021 : Sbornik statei Vserossiiskoi shkoly-seminara. Pod red. An. V. Skripalia [An. V. Skripal, ed. Methods of Computer Diagnostics in Biology and Medicine – 2021 : Collection of articles of the All-Russian school-seminar]. Saratov, Izd-vo “Saratovskii istochnik”, 2021, pp. 107–110 (in Russian).
- Volkov I. Yu., Fomin A. V., Mayskov D. I., Skripal An. V., Sagaidachnyi A. A. Imaging photoplethysmography of hemodynamics and oximetryusing optical clearing of human skin. Yu. N. Dubnishcheva, N. M. Skornyakovoi, eds. Optical Methods of Flow Investigation : Proceedings of the XVI International Scientific and Technical Conference. Moscow, Pero Publ., 2021, pp. 107–113 (in Russian).
- Sun Y., Hu S., Azorin-Peris V., Kalawsky R., Greenwald S. Noncontact imaging photoplethysmography to effectively access pulse rate variability. Journal of Biomedical Optics, 2013, vol. 18, no. 6, e061205. https://www.doi.org/10.1117/1.JBO.18.6.061205
- Taranov A. A., Spiridonov I. N. Contactless photoplethysmography and arterial pulse rate measurements by means of a webcam. Biomeditsinskaya radioelektronika [Biomedical Radioelectronics], 2014, no. 10, pp. 71–80 (in Russian).
- Kublanov V., Purtov K., Belkov D. Remote Photoplethysmography for the Neuro-electrostimulation Procedures Monitoring. Science and Technology Publications, 2017, vol. 4, pp. 307–314. https://www.doi.org/10.5220/0006176003070314
- Kopeliovich M. V., Petrushan M. V. Optimal Facial Areas for Webcam-Based Photoplethysmography. Pattern Recognition and Image Analysis (Advances in Mathematical Theory and Applications), 2016, vol. 26, no. 1, pp. 150–154. https://www.doi.org/10.1134/S1054661816010120
- Imms R., Hu S., Azorin-Peris V., Trico M., Summers R. A high performance biometric signal and image processing method to reveal blood perfusion towards 3D oxygen saturation mapping. The International Society for Optical Engineering, 2014, vol. 8947. https://www.doi.org/10.1117/12.2044318
- Blazek C. R., Merk H. F., Schmid-Schoenbein H., Huelsbusch M., Blazek V. Assessment of allergic skin reactions and their inhibition by antihistamines using photoplethysmography imaging (ppgi). J. Allergy Clin. Immun., 2006, vol. 117, no. 2, pp. S226. https://www.doi.org/10.1016/j.jaci.2005.12.894
- Hulsbusch M., Blazek V. Contactless mapping of rhythmical phenomena in tissue perfusion using ppgi. Proc. SPIE, 2002, vol. 4683, pp. 110–117. https://www.doi.org/10.1117/12.463573
- Wieringa F. P., Mastik F. Remote Non-invasive Stereoscopic Imaging of Blood Vessels : First In-vivo Results of a New Multispectral Contrast Enhancement Technology. Annals of Biomedical Engineering, 2006, vol. 34, no. 12, pp. 1870–1878. https://www.doi.org/10.1007/s10439-006-9198-1
- Kobayashi L., Chuck C. C., Kim C. K., Luchette K. R., Oster BS. A., Merck D. L., Kirenko I., Zon K. V., Bartula M., Rocque M., Wang H., Capraro G. A. Pilot Study of Emergency Department Patient Vital Signs Acquisition Using Experimental Video Photoplethysmography and Passive Infrared Thermography Devices. 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). IEEE, 2019, pp. 0023–0032. https://www.doi.org/10.1109/UEMCON47517.2019.8993087
- Cho Y., Julier S. J., Bianchi-Berthouze N. Instant stress : Detection of perceived mental stress through smartphone photoplethysmography and thermal imaging. JMIR Mental Health, 2019, vol. 6, no. 4, e10140. https://www.doi.org/10.2196/10140
- Blanik N., Abbas A. K., Venema B., Blazek V., Leonhardt S. Hybrid optical imaging technology for long-term remote monitoring of skin perfusion and temperature behavior. Journal of Biomedical Optics, 2014, vol. 19, no. 1, e016012. https://www.doi.org/10.1117/1.JBO.19.1.016012
- Paul M., Behr S. C., Weiss C., Heimann K., Orlikowsky T., Leonhardt S. Spatio-temporal and-spectral feature maps in photoplethysmography imaging and infrared thermograph. BioMedical Engineering OnLine, 2021, vol. 20, no. 1, pp. 1–54. https://www.doi.org/10.1186/s12938-020-00841-9
- Humphreys K., Ward T., Markham C. Noncontact simultaneous dual wavelength photoplethysmography : A further step toward noncontact pulse oximetry. Review of Scientific Instruments, 2007, vol. 78, no. 4, e044304. https://www.doi.org/10.1063/1.2724789
- Kong L., Zhao Y. Non-contact detection of oxygen saturation based on visible light imaging device using ambient light. Optics Express, 2013, vol. 21, no. 15, pp. 17464–17471. https://www.doi.org/10.1364/OE.21.017464
- Shao D., Liu C. Noncontact Monitoring of Blood Oxygen Saturation Using Camera and Dual Wavelength Imaging System. IEEE Transactions on Biomedical Engineering, 2016, vol. 63, no. 6, pp. 1091–1098. https:// www.doi.org/10.1109/TBME.2015.2481896
- Foroughian F., Bauder C. J. The Wavelength Selection for Calibrating Non Contact Detection of Blood Oxygen Satuartion using Imaging Photoplethysmography. 2018 United States National Committee of URSI National Radio Science Meeting (USNC-URSI NRSM), 2018, pp. 1–2.
- Moco A., Verkruysse W. Pulse oximetry based on photoplethysmography imaging with red and green light. Journal of Clinical Monitoring and Computing, 2021, vol. 35, no. 1, pp. 123–133. https://www.doi.org/10.1007/s10877-019-00449-y
- Gastel M., Wang W., Verkruysse W. Reducing the effects of parallax in camera-based pulse-oximetry. Biomedical Optics Express, 2021, vol. 12, no. 5, pp. 2813–2824. https://www.doi.org/10.1364/BOE.419199
- Gastel M., Verkruysse W., Haan G. Data-driven calibration estimation for robust remote pulse-oximetry. Appl. Sci., 2019, vol. 9, no. 18, e3857. https://www.doi.org/10.3390/app9183857
- Bal U. Non-contact estimation of heart rate and oxygen saturation using ambient light. Biomedical Optics Express, 2015, vol. 6, no. 1, pp. 86–97. https://www.doi.org/10.1364/BOE.6.000086
- Freitas U. S. Remote Camera-based Pulse Oximetry. The Sixth International Conference on eHealth, Telemedicine, and Social Medicine. International Academy, Research and Industry Association (IARIA), 2014, pp. 59–63.
- Guazzi A. R., Villarroel M. Non-contact measurement of oxygen saturation with an RGB camera. Biomedical Optics Express, 2015, vol. 6, no. 9, pp. 3320–3338. https://www.doi.org/10.1364/BOE.6.003320
- Addison P. S. Modular continuous wavelet processing of biosignals : Extracting heart rate and oxygen saturation from a video signal. Healthcare Technology Letters, 2016, vol. 3, no. 2, pp. 1–6. https://www.doi.org/10.1049/htl.2015.0052
- Mathew J., Tian X., Wu M. Remote Blood Oxygen Estimation From Videos Using Neural Networks. 2021. arXiv:2107.05087.
- Ali A.-N., Khalid G. A. Non-Contact SpO2 Prediction System Based on a Digital Camera. Appl. Sci., 2021, vol. 11, no. 9, e4255. https://www.doi.org/10.3390/app11094255
- Tuchin V. V. Tissue Optics, Light Scattering Methods and Instruments for Medical Diagnosis. Society of Photo Optical, 2015. 988 p. (Russ. ed. : Tuchin V. V. Optika biologicheskikh tkanei : Metody rasseyaniya sveta v meditsinskoi diagnostike. Moscow : OOO Izdatel’skaya firma “Fiziko-matematicheskaya literatura”, 2013. 812 p.)
- 3785 reads