Direct-Global Separation for Improved Imaging Photoplethysmography

Camera-based estimation of vital signs has made significant progress in last few years. Despite of the significant algorithmic advances, the low signal-to-background ratio in video-based photoplethysmography continues to be a performance bottleneck. One of the main challenges is that much of the light returning to the camera from the subject is surface reflection from the skin and other dermal layers, and hence does not contain any pulsatile blood perfusion information to estimate photoplesthysmogram (PPG). In this paper, we show that direct-global separation techniques designed to reject much of the surface reflection photons can improve the signal-to-background ratio in the raw captured video signal. We study two techniques for the suppression of direct surface reflection (a) cross-polarization and (b) structured illumination. Using a dataset from 28 participants, our results show an average SNR improvement in estimating PPG from the use of structured illumination is 1.42 dB compared to the brightfield illumination. The use of cross-polarizers leads to an average SNR increase of 1.49 dB compared to brightfield illumination. And the combined structured illumination and polarizer method increases the SNR on the average by 1.90 dB compared to the brightfield illumination. The key result is that local PPG estimate SNR can increase to more than 5.63dB, enabling very large gains on regions with a large specular component. The RMSE decreased 55% and the range of error reduced by 12.9% with the use of a polarizer and structured illumination.

[1]  Rana El Kaliouby,et al.  Supervised learning approach to remote heart rate estimation from facial videos , 2015, 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).

[2]  Ashok Veeraraghavan,et al.  A Practical Approach to 3D Scanning in the Presence of Interreflections, Subsurface Scattering and Defocus , 2013, International Journal of Computer Vision.

[3]  Jessica C Ramella-Roman,et al.  Imaging skin pathology with polarized light. , 2002, Journal of biomedical optics.

[4]  Winston H. Hsu,et al.  Learning-based heart rate detection from remote photoplethysmography features , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[5]  Gerard de Haan,et al.  Robust Pulse Rate From Chrominance-Based rPPG , 2013, IEEE Transactions on Biomedical Engineering.

[6]  R. Alfano,et al.  Optical polarization imaging. , 1997, Applied optics.

[7]  Sander Stuijk,et al.  Amplitude-selective filtering for remote-PPG. , 2017, Biomedical optics express.

[8]  R. Romashko,et al.  A new look at the essence of the imaging photoplethysmography , 2015, Scientific Reports.

[9]  L. O. Svaasand,et al.  Remote plethysmographic imaging using ambient light. , 2008, Optics express.

[10]  D. G. Brennan,et al.  Linear diversity combining techniques , 2003 .

[11]  Ashok Veeraraghavan,et al.  DistancePPG: Robust non-contact vital signs monitoring using a camera , 2015, Biomedical optics express.

[12]  Peter J Lesniewski,et al.  Signal recovery in imaging photoplethysmography , 2013, Physiological measurement.

[13]  Sijung Hu,et al.  Opto-physiological modeling applied to photoplethysmographic cardiovascular assessment. , 2013, Journal of healthcare engineering.

[14]  Matthew O'Toole,et al.  3D Shape and Indirect Appearance by Structured Light Transport , 2014, CVPR.

[15]  Rosalind W. Picard,et al.  Non-contact, automated cardiac pulse measurements using video imaging and blind source separation , 2022 .

[16]  M. Elgendi On the Analysis of Fingertip Photoplethysmogram Signals , 2012, Current cardiology reviews.

[17]  Hagen Malberg,et al.  The value of polarization in camera-based photoplethysmography. , 2017, Biomedical optics express.

[18]  Paul E. Debevec,et al.  Acquiring the reflectance field of a human face , 2000, SIGGRAPH.

[19]  Steven L. Jacques,et al.  Polarized video imaging of skin , 1998, Photonics West - Biomedical Optics.

[20]  Kwang Suk Park,et al.  Validation of heart rate extraction using video imaging on a built-in camera system of a smartphone , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[21]  D. Haan,et al.  Improved motion robustness of remote-PPG by using the blood volume pulse signature , 2014 .

[22]  L. Tarassenko,et al.  Non-contact video-based vital sign monitoring using ambient light and auto-regressive models , 2014, Physiological measurement.

[23]  Ashok Veeraraghavan,et al.  PulseCam: High-resolution blood perfusion imaging using a camera and a pulse oximeter , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[24]  Ramesh Raskar,et al.  Fast separation of direct and global components of a scene using high frequency illumination , 2006, ACM Trans. Graph..

[25]  Igor S Sidorov,et al.  Influence of polarization filtration on the information readout from pulsating blood vessels. , 2016, Biomedical optics express.

[26]  F. Mastik,et al.  Contactless Multiple Wavelength Photoplethysmographic Imaging: A First Step Toward “SpO2 Camera” Technology , 2005, Annals of Biomedical Engineering.

[27]  E. Hari Krishna,et al.  A Novel Approach for Motion Artifact Reduction in PPG Signals Based on AS-LMS Adaptive Filter , 2012, IEEE Transactions on Instrumentation and Measurement.

[28]  Yu Sun,et al.  Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise. , 2011, Journal of biomedical optics.

[29]  Roozbeh Jafari,et al.  Robust heart rate estimation using wrist-based PPG signals in the presence of intense physical activities , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[30]  Anthony J. Durkin,et al.  Quantitation and mapping of tissue optical properties using modulated imaging. , 2009, Journal of biomedical optics.

[31]  Yu Sun,et al.  Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging , 2016, IEEE Transactions on Biomedical Engineering.

[32]  Terrance E. Boult,et al.  Constraining Object Features Using a Polarization Reflectance Model , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[33]  Srinivasa G. Narasimhan,et al.  Compensating for Motion during Direct-Global Separation , 2013, 2013 IEEE International Conference on Computer Vision.

[34]  Daniel McDuff,et al.  Advancements in Noncontact, Multiparameter Physiological Measurements Using a Webcam , 2011, IEEE Transactions on Biomedical Engineering.