Direct-global separation for improved imaging photoplethysmography

Jaehee Park, Ashutosh Sabharwal, Ashok Veeraraghavan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1456-1465
Number of pages10
ISBN (Electronic)9781538661000
DOIs
StatePublished - Dec 13 2018
Event31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018 - Salt Lake City, United States
Duration: Jun 18 2018Jun 22 2018

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2018-June
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018
Country/TerritoryUnited States
CitySalt Lake City
Period6/18/186/22/18

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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