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Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life
The photoplethysmographic (PPG) signal has been applied in various research fields, with promising results for its future clinical application. However, there are several sources of variability that, if not adequately controlled, can hamper its application in pervasive monitoring contexts. This stud...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300860/ https://www.ncbi.nlm.nih.gov/pubmed/35873348 http://dx.doi.org/10.3389/fdgth.2022.912353 |
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author | Moscato, Serena Palmerini, Luca Palumbo, Pierpaolo Chiari, Lorenzo |
author_facet | Moscato, Serena Palmerini, Luca Palumbo, Pierpaolo Chiari, Lorenzo |
author_sort | Moscato, Serena |
collection | PubMed |
description | The photoplethysmographic (PPG) signal has been applied in various research fields, with promising results for its future clinical application. However, there are several sources of variability that, if not adequately controlled, can hamper its application in pervasive monitoring contexts. This study assessed and characterized the impact of several sources of variability, such as physical activity, age, sex, and health state on PPG signal quality and PPG waveform parameters (Rise Time, Pulse Amplitude, Pulse Time, Reflection Index, Delta T, and DiastolicAmplitude). We analyzed 31 24 h recordings by as many participants (19 healthy subjects and 12 oncological patients) with a wristband wearable device, selecting a set of PPG pulses labeled with three different quality levels. We implemented a Multinomial Logistic Regression (MLR) model to evaluate the impact of the aforementioned factors on PPG signal quality. We then extracted six parameters only on higher-quality PPG pulses and evaluated the influence of physical activity, age, sex, and health state on these parameters with Generalized Linear Mixed Effects Models (GLMM). We found that physical activity has a detrimental effect on PPG signal quality quality (94% of pulses with good quality when the subject is at rest vs. 9% during intense activity), and that health state affects the percentage of available PPG pulses of the best quality (at rest, 44% for healthy subjects vs. 13% for oncological patients). Most of the extracted parameters are influenced by physical activity and health state, while age significantly impacts two parameters related to arterial stiffness. These results can help expand the awareness that accurate, reliable information extracted from PPG signals can be reached by tackling and modeling different sources of inaccuracy. |
format | Online Article Text |
id | pubmed-9300860 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93008602022-07-22 Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life Moscato, Serena Palmerini, Luca Palumbo, Pierpaolo Chiari, Lorenzo Front Digit Health Digital Health The photoplethysmographic (PPG) signal has been applied in various research fields, with promising results for its future clinical application. However, there are several sources of variability that, if not adequately controlled, can hamper its application in pervasive monitoring contexts. This study assessed and characterized the impact of several sources of variability, such as physical activity, age, sex, and health state on PPG signal quality and PPG waveform parameters (Rise Time, Pulse Amplitude, Pulse Time, Reflection Index, Delta T, and DiastolicAmplitude). We analyzed 31 24 h recordings by as many participants (19 healthy subjects and 12 oncological patients) with a wristband wearable device, selecting a set of PPG pulses labeled with three different quality levels. We implemented a Multinomial Logistic Regression (MLR) model to evaluate the impact of the aforementioned factors on PPG signal quality. We then extracted six parameters only on higher-quality PPG pulses and evaluated the influence of physical activity, age, sex, and health state on these parameters with Generalized Linear Mixed Effects Models (GLMM). We found that physical activity has a detrimental effect on PPG signal quality quality (94% of pulses with good quality when the subject is at rest vs. 9% during intense activity), and that health state affects the percentage of available PPG pulses of the best quality (at rest, 44% for healthy subjects vs. 13% for oncological patients). Most of the extracted parameters are influenced by physical activity and health state, while age significantly impacts two parameters related to arterial stiffness. These results can help expand the awareness that accurate, reliable information extracted from PPG signals can be reached by tackling and modeling different sources of inaccuracy. Frontiers Media S.A. 2022-07-07 /pmc/articles/PMC9300860/ /pubmed/35873348 http://dx.doi.org/10.3389/fdgth.2022.912353 Text en Copyright © 2022 Moscato, Palmerini, Palumbo and Chiari. 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 Moscato, Serena Palmerini, Luca Palumbo, Pierpaolo Chiari, Lorenzo Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life |
title | Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life |
title_full | Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life |
title_fullStr | Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life |
title_full_unstemmed | Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life |
title_short | Quality Assessment and Morphological Analysis of Photoplethysmography in Daily Life |
title_sort | quality assessment and morphological analysis of photoplethysmography in daily life |
topic | Digital Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300860/ https://www.ncbi.nlm.nih.gov/pubmed/35873348 http://dx.doi.org/10.3389/fdgth.2022.912353 |
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