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Advancing PPG Signal Quality and Know-How Through Knowledge Translation—From Experts to Student and Researcher
Objective: Despite the vast number of photoplethysmography (PPG) research publications and growing demands for such sensing in Digital and Wearable Health platforms, there appears little published on signal quality expectations for morphological pulse analysis. Aim: to determine a consensus regardin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521847/ https://www.ncbi.nlm.nih.gov/pubmed/34713077 http://dx.doi.org/10.3389/fdgth.2020.619692 |
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author | Huthart, Samuel Elgendi, Mohamed Zheng, Dingchang Stansby, Gerard Allen, John |
author_facet | Huthart, Samuel Elgendi, Mohamed Zheng, Dingchang Stansby, Gerard Allen, John |
author_sort | Huthart, Samuel |
collection | PubMed |
description | Objective: Despite the vast number of photoplethysmography (PPG) research publications and growing demands for such sensing in Digital and Wearable Health platforms, there appears little published on signal quality expectations for morphological pulse analysis. Aim: to determine a consensus regarding the minimum number of undistorted i.e., diagnostic quality pulses required, as well as a threshold proportion of noisy beats for recording rejection. Approach: Questionnaire distributed to international fellow researchers in skin contact PPG measurements on signal quality expectations and associated factors concerning recording length, expected artifact-free pulses (“diagnostic quality”) in a trace, proportion of trace having artifact to justify excluding/repeating measurements, minimum beats required, and number of respiratory cycles. Main Results: 18 (of 26) PPG researchers responded. Modal range estimates considered a 2-min recording time as target for morphological analysis. Respondents expected a recording to have 86–95% of diagnostic quality pulses, at least 11–20 sequential pulses of diagnostic quality and advocated a 26–50% noise threshold for recording rejection. There were broader responses found for the required number of undistorted beats (although a modal range of 51–60 beats for both finger and toe sites was indicated). Significance: For morphological PPG pulse wave analysis recording acceptability was indicated if <50% of beats have artifact and preferably that a minimum of 50 non-distorted PPG pulses are present (with at least 11–20 sequential) to be of diagnostic quality. Estimates from this knowledge transfer exercise should help inform students and researchers as a guide in standards development for PPG study design. |
format | Online Article Text |
id | pubmed-8521847 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85218472021-10-27 Advancing PPG Signal Quality and Know-How Through Knowledge Translation—From Experts to Student and Researcher Huthart, Samuel Elgendi, Mohamed Zheng, Dingchang Stansby, Gerard Allen, John Front Digit Health Digital Health Objective: Despite the vast number of photoplethysmography (PPG) research publications and growing demands for such sensing in Digital and Wearable Health platforms, there appears little published on signal quality expectations for morphological pulse analysis. Aim: to determine a consensus regarding the minimum number of undistorted i.e., diagnostic quality pulses required, as well as a threshold proportion of noisy beats for recording rejection. Approach: Questionnaire distributed to international fellow researchers in skin contact PPG measurements on signal quality expectations and associated factors concerning recording length, expected artifact-free pulses (“diagnostic quality”) in a trace, proportion of trace having artifact to justify excluding/repeating measurements, minimum beats required, and number of respiratory cycles. Main Results: 18 (of 26) PPG researchers responded. Modal range estimates considered a 2-min recording time as target for morphological analysis. Respondents expected a recording to have 86–95% of diagnostic quality pulses, at least 11–20 sequential pulses of diagnostic quality and advocated a 26–50% noise threshold for recording rejection. There were broader responses found for the required number of undistorted beats (although a modal range of 51–60 beats for both finger and toe sites was indicated). Significance: For morphological PPG pulse wave analysis recording acceptability was indicated if <50% of beats have artifact and preferably that a minimum of 50 non-distorted PPG pulses are present (with at least 11–20 sequential) to be of diagnostic quality. Estimates from this knowledge transfer exercise should help inform students and researchers as a guide in standards development for PPG study design. Frontiers Media S.A. 2020-12-21 /pmc/articles/PMC8521847/ /pubmed/34713077 http://dx.doi.org/10.3389/fdgth.2020.619692 Text en Copyright © 2020 Huthart, Elgendi, Zheng, Stansby and Allen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Digital Health Huthart, Samuel Elgendi, Mohamed Zheng, Dingchang Stansby, Gerard Allen, John Advancing PPG Signal Quality and Know-How Through Knowledge Translation—From Experts to Student and Researcher |
title | Advancing PPG Signal Quality and Know-How Through Knowledge Translation—From Experts to Student and Researcher |
title_full | Advancing PPG Signal Quality and Know-How Through Knowledge Translation—From Experts to Student and Researcher |
title_fullStr | Advancing PPG Signal Quality and Know-How Through Knowledge Translation—From Experts to Student and Researcher |
title_full_unstemmed | Advancing PPG Signal Quality and Know-How Through Knowledge Translation—From Experts to Student and Researcher |
title_short | Advancing PPG Signal Quality and Know-How Through Knowledge Translation—From Experts to Student and Researcher |
title_sort | advancing ppg signal quality and know-how through knowledge translation—from experts to student and researcher |
topic | Digital Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521847/ https://www.ncbi.nlm.nih.gov/pubmed/34713077 http://dx.doi.org/10.3389/fdgth.2020.619692 |
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