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Temporal complexity in photoplethysmography and its influence on blood pressure

Objective: The temporal complexity of photoplethysmography (PPG) provides valuable information about blood pressure (BP). In this study, we aim to interpret the stochastic PPG patterns with a model-based simulation, which may help optimize the BP estimation algorithms. Methods: The classic four-elem...

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Autores principales: Xing, Xiaoman, Huang, Rui, Hao, Liling, Jiang, Chenyu, Dong, Wen-Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513039/
https://www.ncbi.nlm.nih.gov/pubmed/37745247
http://dx.doi.org/10.3389/fphys.2023.1187561
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author Xing, Xiaoman
Huang, Rui
Hao, Liling
Jiang, Chenyu
Dong, Wen-Fei
author_facet Xing, Xiaoman
Huang, Rui
Hao, Liling
Jiang, Chenyu
Dong, Wen-Fei
author_sort Xing, Xiaoman
collection PubMed
description Objective: The temporal complexity of photoplethysmography (PPG) provides valuable information about blood pressure (BP). In this study, we aim to interpret the stochastic PPG patterns with a model-based simulation, which may help optimize the BP estimation algorithms. Methods: The classic four-element Windkessel model is adapted in this study to incorporate BP-dependent compliance profiles. Simulations are performed to generate PPG responses to pulse and continuous stimuli at various timescales, aiming to mimic sudden or gradual hemodynamic changes observed in real-life scenarios. To quantify the temporal complexity of PPG, we utilize the Higuchi fractal dimension (HFD) and autocorrelation function (ACF). These measures provide insights into the intricate temporal patterns exhibited by PPG. To validate the simulation results, continuous recordings of BP, PPG, and stroke volume from 40 healthy subjects were used. Results: Pulse simulations showed that central vascular compliance variation during a cardiac cycle, peripheral resistance, and cardiac output (CO) collectively contributed to the time delay, amplitude overshoot, and phase shift of PPG responses. Continuous simulations showed that the PPG complexity could be generated by random stimuli, which were subsequently influenced by the autocorrelation patterns of the stimuli. Importantly, the relationship between complexity and hemodynamics as predicted by our model aligned well with the experimental analysis. HFD and ACF had significant contributions to BP, displaying stability even in the presence of high CO fluctuations. In contrast, morphological features exhibited reduced contribution in unstable hemodynamic conditions. Conclusion: Temporal complexity patterns are essential to single-site PPG-based BP estimation. Understanding the physiological implications of these patterns can aid in the development of algorithms with clear interpretability and optimal structures.
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spelling pubmed-105130392023-09-22 Temporal complexity in photoplethysmography and its influence on blood pressure Xing, Xiaoman Huang, Rui Hao, Liling Jiang, Chenyu Dong, Wen-Fei Front Physiol Physiology Objective: The temporal complexity of photoplethysmography (PPG) provides valuable information about blood pressure (BP). In this study, we aim to interpret the stochastic PPG patterns with a model-based simulation, which may help optimize the BP estimation algorithms. Methods: The classic four-element Windkessel model is adapted in this study to incorporate BP-dependent compliance profiles. Simulations are performed to generate PPG responses to pulse and continuous stimuli at various timescales, aiming to mimic sudden or gradual hemodynamic changes observed in real-life scenarios. To quantify the temporal complexity of PPG, we utilize the Higuchi fractal dimension (HFD) and autocorrelation function (ACF). These measures provide insights into the intricate temporal patterns exhibited by PPG. To validate the simulation results, continuous recordings of BP, PPG, and stroke volume from 40 healthy subjects were used. Results: Pulse simulations showed that central vascular compliance variation during a cardiac cycle, peripheral resistance, and cardiac output (CO) collectively contributed to the time delay, amplitude overshoot, and phase shift of PPG responses. Continuous simulations showed that the PPG complexity could be generated by random stimuli, which were subsequently influenced by the autocorrelation patterns of the stimuli. Importantly, the relationship between complexity and hemodynamics as predicted by our model aligned well with the experimental analysis. HFD and ACF had significant contributions to BP, displaying stability even in the presence of high CO fluctuations. In contrast, morphological features exhibited reduced contribution in unstable hemodynamic conditions. Conclusion: Temporal complexity patterns are essential to single-site PPG-based BP estimation. Understanding the physiological implications of these patterns can aid in the development of algorithms with clear interpretability and optimal structures. Frontiers Media S.A. 2023-08-31 /pmc/articles/PMC10513039/ /pubmed/37745247 http://dx.doi.org/10.3389/fphys.2023.1187561 Text en Copyright © 2023 Xing, Huang, Hao, Jiang and Dong. 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 Physiology
Xing, Xiaoman
Huang, Rui
Hao, Liling
Jiang, Chenyu
Dong, Wen-Fei
Temporal complexity in photoplethysmography and its influence on blood pressure
title Temporal complexity in photoplethysmography and its influence on blood pressure
title_full Temporal complexity in photoplethysmography and its influence on blood pressure
title_fullStr Temporal complexity in photoplethysmography and its influence on blood pressure
title_full_unstemmed Temporal complexity in photoplethysmography and its influence on blood pressure
title_short Temporal complexity in photoplethysmography and its influence on blood pressure
title_sort temporal complexity in photoplethysmography and its influence on blood pressure
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10513039/
https://www.ncbi.nlm.nih.gov/pubmed/37745247
http://dx.doi.org/10.3389/fphys.2023.1187561
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