Literature DB >> 25159049

Improved motion robustness of remote-PPG by using the blood volume pulse signature.

G de Haan1, A van Leest.   

Abstract

Remote photoplethysmography (rPPG) enables contact-free monitoring of the blood volume pulse using a color camera. Essentially, it detects the minute optical absorption changes caused by blood volume variations in the skin. In this paper, we show that the different absorption spectra of arterial blood and bloodless skin cause the variations to occur along a very specific vector in a normalized RGB-space. The exact vector can be determined for a given light spectrum and for given transfer characteristics of the optical filters in the camera. We show that this 'signature' can be used to design an rPPG algorithm with a much better motion robustness than the recent methods based on blind source separation, and even better than the chrominance-based methods we published earlier. Using six videos recorded in a gym, with four subjects exercising on a range of fitness devices, we confirm the superior motion robustness of our newly proposed rPPG methods. A simple peak detector in the frequency domain returns the correct pulse-rate for 68% of total measurements compared to 60% for the best previous method, while the SNR of the pulse-signal improves from  - 5 dB to  - 4 dB. For a large population of 117 stationary subjects we prove that the accuracy is comparable to the best previous method, although the SNR of the pulse-signal drops from  + 8.4 dB to  + 7.6 dB. We expect the improved motion robustness to significantly widen the application scope of the rPPG-technique.

Entities:  

Year:  2014        PMID: 25159049     DOI: 10.1088/0967-3334/35/9/1913

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  34 in total

1.  Robust respiration detection from remote photoplethysmography.

Authors:  Mark van Gastel; Sander Stuijk; Gerard de Haan
Journal:  Biomed Opt Express       Date:  2016-11-03       Impact factor: 3.732

2.  Spectral-spatial fusion model for robust blood pulse waveform extraction in photoplethysmographic imaging.

Authors:  Robert Amelard; David A Clausi; Alexander Wong
Journal:  Biomed Opt Express       Date:  2016-11-01       Impact factor: 3.732

3.  Skin inhomogeneity as a source of error in remote PPG-imaging.

Authors:  Andreia Vieira Moço; Sander Stuijk; Gerard de Haan
Journal:  Biomed Opt Express       Date:  2016-10-26       Impact factor: 3.732

4.  Full video pulse extraction.

Authors:  Wenjin Wang; Albertus C den Brinker; Gerard de Haan
Journal:  Biomed Opt Express       Date:  2018-07-27       Impact factor: 3.732

5.  Amplitude-selective filtering for remote-PPG.

Authors:  Wenjin Wang; Albertus C den Brinker; Sander Stuijk; Gerard de Haan
Journal:  Biomed Opt Express       Date:  2017-02-28       Impact factor: 3.732

6.  Analysis of CNN-based remote-PPG to understand limitations and sensitivities.

Authors:  Qi Zhan; Wenjin Wang; Gerard de Haan
Journal:  Biomed Opt Express       Date:  2020-02-07       Impact factor: 3.732

Review 7.  Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging.

Authors:  Yu Sun; Nitish Thakor
Journal:  IEEE Trans Biomed Eng       Date:  2015-09-15       Impact factor: 4.538

8.  Simultaneous Tracking of Cardiorespiratory Signals for Multiple Persons Using a Machine Vision System With Noise Artifact Removal.

Authors:  Ali Al-Naji; Javaan Chahl
Journal:  IEEE J Transl Eng Health Med       Date:  2017-09-29       Impact factor: 3.316

9.  Non-contact measurement of oxygen saturation with an RGB camera.

Authors:  Alessandro R Guazzi; Mauricio Villarroel; João Jorge; Jonathan Daly; Matthew C Frise; Peter A Robbins; Lionel Tarassenko
Journal:  Biomed Opt Express       Date:  2015-08-11       Impact factor: 3.732

10.  Evaluation of biases in remote photoplethysmography methods.

Authors:  Ananyananda Dasari; Sakthi Kumar Arul Prakash; László A Jeni; Conrad S Tucker
Journal:  NPJ Digit Med       Date:  2021-06-03
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