Evaluation of biases in remote photoplethysmography methods

Abstract This work investigates the estimation biases of remote photoplethysmography (rPPG) methods for pulse rate measurement across diverse demographics. Advances in photoplethysmography (PPG) and rPPG methods have enabled the development of contact and noncontact approaches for continuous monitor...

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Autores principales:	Ananyananda Dasari, Sakthi Kumar Arul Prakash, László A. Jeni, Conrad S. Tucker
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/250d736043c9468b828363cca852ddc6
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spelling	oai:doaj.org-article:250d736043c9468b828363cca852ddc62021-12-02T15:02:32ZEvaluation of biases in remote photoplethysmography methods10.1038/s41746-021-00462-z2398-6352https://doaj.org/article/250d736043c9468b828363cca852ddc62021-06-01T00:00:00Zhttps://doi.org/10.1038/s41746-021-00462-zhttps://doaj.org/toc/2398-6352Abstract This work investigates the estimation biases of remote photoplethysmography (rPPG) methods for pulse rate measurement across diverse demographics. Advances in photoplethysmography (PPG) and rPPG methods have enabled the development of contact and noncontact approaches for continuous monitoring and collection of patient health data. The contagious nature of viruses such as COVID-19 warrants noncontact methods for physiological signal estimation. However, these approaches are subject to estimation biases due to variations in environmental conditions and subject demographics. The performance of contact-based wearable sensors has been evaluated, using off-the-shelf devices across demographics. However, the measurement uncertainty of rPPG methods that estimate pulse rate has not been sufficiently tested across diverse demographic populations or environments. Quantifying the efficacy of rPPG methods in real-world conditions is critical in determining their potential viability as health monitoring solutions. Currently, publicly available face datasets accompanied by physiological measurements are typically captured in controlled laboratory settings, lacking diversity in subject skin tones, age, and cultural artifacts (e.g, bindi worn by Indian women). In this study, we collect pulse rate and facial video data from human subjects in India and Sierra Leone, in order to quantify the uncertainty in noncontact pulse rate estimation methods. The video data are used to estimate pulse rate using state-of-the-art rPPG camera-based methods, and compared against ground truth measurements captured using an FDA-approved contact-based pulse rate measurement device. Our study reveals that rPPG methods exhibit similar biases when compared with a contact-based device across demographic groups and environmental conditions. The mean difference between pulse rates measured by rPPG methods and the ground truth is found to be ~2% (1 beats per minute (b.p.m.)), signifying agreement of rPPG methods with the ground truth. We also find that rPPG methods show pulse rate variability of ~15% (11 b.p.m.), as compared to the ground truth. We investigate factors impacting rPPG methods and discuss solutions aimed at mitigating variance.Ananyananda DasariSakthi Kumar Arul PrakashLászló A. JeniConrad S. TuckerNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 4, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Ananyananda Dasari Sakthi Kumar Arul Prakash László A. Jeni Conrad S. Tucker Evaluation of biases in remote photoplethysmography methods
description	Abstract This work investigates the estimation biases of remote photoplethysmography (rPPG) methods for pulse rate measurement across diverse demographics. Advances in photoplethysmography (PPG) and rPPG methods have enabled the development of contact and noncontact approaches for continuous monitoring and collection of patient health data. The contagious nature of viruses such as COVID-19 warrants noncontact methods for physiological signal estimation. However, these approaches are subject to estimation biases due to variations in environmental conditions and subject demographics. The performance of contact-based wearable sensors has been evaluated, using off-the-shelf devices across demographics. However, the measurement uncertainty of rPPG methods that estimate pulse rate has not been sufficiently tested across diverse demographic populations or environments. Quantifying the efficacy of rPPG methods in real-world conditions is critical in determining their potential viability as health monitoring solutions. Currently, publicly available face datasets accompanied by physiological measurements are typically captured in controlled laboratory settings, lacking diversity in subject skin tones, age, and cultural artifacts (e.g, bindi worn by Indian women). In this study, we collect pulse rate and facial video data from human subjects in India and Sierra Leone, in order to quantify the uncertainty in noncontact pulse rate estimation methods. The video data are used to estimate pulse rate using state-of-the-art rPPG camera-based methods, and compared against ground truth measurements captured using an FDA-approved contact-based pulse rate measurement device. Our study reveals that rPPG methods exhibit similar biases when compared with a contact-based device across demographic groups and environmental conditions. The mean difference between pulse rates measured by rPPG methods and the ground truth is found to be ~2% (1 beats per minute (b.p.m.)), signifying agreement of rPPG methods with the ground truth. We also find that rPPG methods show pulse rate variability of ~15% (11 b.p.m.), as compared to the ground truth. We investigate factors impacting rPPG methods and discuss solutions aimed at mitigating variance.
format	article
author	Ananyananda Dasari Sakthi Kumar Arul Prakash László A. Jeni Conrad S. Tucker
author_facet	Ananyananda Dasari Sakthi Kumar Arul Prakash László A. Jeni Conrad S. Tucker
author_sort	Ananyananda Dasari
title	Evaluation of biases in remote photoplethysmography methods
title_short	Evaluation of biases in remote photoplethysmography methods
title_full	Evaluation of biases in remote photoplethysmography methods
title_fullStr	Evaluation of biases in remote photoplethysmography methods
title_full_unstemmed	Evaluation of biases in remote photoplethysmography methods
title_sort	evaluation of biases in remote photoplethysmography methods
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/250d736043c9468b828363cca852ddc6
work_keys_str_mv	AT ananyanandadasari evaluationofbiasesinremotephotoplethysmographymethods AT sakthikumararulprakash evaluationofbiasesinremotephotoplethysmographymethods AT laszloajeni evaluationofbiasesinremotephotoplethysmographymethods AT conradstucker evaluationofbiasesinremotephotoplethysmographymethods
_version_	1718389064913125376

Evaluation of biases in remote photoplethysmography methods

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