A calibration method for smartphone camera photophlethysmography
Smartphone camera photoplethysmography (cPPG) enables non-invasive pulse oximetry and hemoglobin concentration measurements. However, the aesthetic-driven non-linearity in default image capture and preprocessing pipelines poses challenges for consistency and transferability of cPPG across devices. T...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Frontiers Media S.A.
2023-11-01
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Series: | Frontiers in Digital Health |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fdgth.2023.1301019/full |
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author | Yinan Xuan Yinan Xuan Colin Barry Colin Barry Nick Antipa Edward Jay Wang Edward Jay Wang |
author_facet | Yinan Xuan Yinan Xuan Colin Barry Colin Barry Nick Antipa Edward Jay Wang Edward Jay Wang |
author_sort | Yinan Xuan |
collection | DOAJ |
description | Smartphone camera photoplethysmography (cPPG) enables non-invasive pulse oximetry and hemoglobin concentration measurements. However, the aesthetic-driven non-linearity in default image capture and preprocessing pipelines poses challenges for consistency and transferability of cPPG across devices. This work identifies two key parameters—tone mapping and sensor threshold—that significantly impact cPPG measurements. We propose a novel calibration method to linearize camera measurements, thus enhancing consistency and transferability of cPPG across devices. A benchtop calibration system is also presented, leveraging a microcontroller and LED setup to characterize these parameters for each phone model. Our validation studies demonstrate that, with appropriate calibration and camera settings, cPPG applications can achieve 74% higher accuracy than with default settings. Moreover, our calibration method proves effective across different smartphone models (N=4), and calibrations performed on one phone can be applied to other smartphones of the same model (N=6), enhancing consistency and scalability of cPPG applications. |
first_indexed | 2024-03-09T16:20:38Z |
format | Article |
id | doaj.art-5e5f9649456f414cad61acfeb8bb4d5a |
institution | Directory Open Access Journal |
issn | 2673-253X |
language | English |
last_indexed | 2024-03-09T16:20:38Z |
publishDate | 2023-11-01 |
publisher | Frontiers Media S.A. |
record_format | Article |
series | Frontiers in Digital Health |
spelling | doaj.art-5e5f9649456f414cad61acfeb8bb4d5a2023-11-24T15:23:24ZengFrontiers Media S.A.Frontiers in Digital Health2673-253X2023-11-01510.3389/fdgth.2023.13010191301019A calibration method for smartphone camera photophlethysmographyYinan Xuan0Yinan Xuan1Colin Barry2Colin Barry3Nick Antipa4Edward Jay Wang5Edward Jay Wang6Electrical and Computer Engineering, UC San Diego, La Jolla, CA, United StatesThe Design Lab, UC San Diego, La Jolla, CA, USAElectrical and Computer Engineering, UC San Diego, La Jolla, CA, United StatesThe Design Lab, UC San Diego, La Jolla, CA, USAElectrical and Computer Engineering, UC San Diego, La Jolla, CA, United StatesElectrical and Computer Engineering, UC San Diego, La Jolla, CA, United StatesThe Design Lab, UC San Diego, La Jolla, CA, USASmartphone camera photoplethysmography (cPPG) enables non-invasive pulse oximetry and hemoglobin concentration measurements. However, the aesthetic-driven non-linearity in default image capture and preprocessing pipelines poses challenges for consistency and transferability of cPPG across devices. This work identifies two key parameters—tone mapping and sensor threshold—that significantly impact cPPG measurements. We propose a novel calibration method to linearize camera measurements, thus enhancing consistency and transferability of cPPG across devices. A benchtop calibration system is also presented, leveraging a microcontroller and LED setup to characterize these parameters for each phone model. Our validation studies demonstrate that, with appropriate calibration and camera settings, cPPG applications can achieve 74% higher accuracy than with default settings. Moreover, our calibration method proves effective across different smartphone models (N=4), and calibrations performed on one phone can be applied to other smartphones of the same model (N=6), enhancing consistency and scalability of cPPG applications.https://www.frontiersin.org/articles/10.3389/fdgth.2023.1301019/fullsmartphonephotoplethysmographycalibrationpulse oximetryhemoglobincamera |
spellingShingle | Yinan Xuan Yinan Xuan Colin Barry Colin Barry Nick Antipa Edward Jay Wang Edward Jay Wang A calibration method for smartphone camera photophlethysmography Frontiers in Digital Health smartphone photoplethysmography calibration pulse oximetry hemoglobin camera |
title | A calibration method for smartphone camera photophlethysmography |
title_full | A calibration method for smartphone camera photophlethysmography |
title_fullStr | A calibration method for smartphone camera photophlethysmography |
title_full_unstemmed | A calibration method for smartphone camera photophlethysmography |
title_short | A calibration method for smartphone camera photophlethysmography |
title_sort | calibration method for smartphone camera photophlethysmography |
topic | smartphone photoplethysmography calibration pulse oximetry hemoglobin camera |
url | https://www.frontiersin.org/articles/10.3389/fdgth.2023.1301019/full |
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