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Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals
Blood pressure measurements are one of the most routinely performed medical tests globally. Blood pressure is an important metric since it provides information that can be used to diagnose several vascular diseases. Conventional blood pressure measurement systems use cuff-based devices to measure th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838459/ https://www.ncbi.nlm.nih.gov/pubmed/35161920 http://dx.doi.org/10.3390/s22031175 |
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author | Haque, Chowdhury Azimul Kwon, Tae-Ho Kim, Ki-Doo |
author_facet | Haque, Chowdhury Azimul Kwon, Tae-Ho Kim, Ki-Doo |
author_sort | Haque, Chowdhury Azimul |
collection | PubMed |
description | Blood pressure measurements are one of the most routinely performed medical tests globally. Blood pressure is an important metric since it provides information that can be used to diagnose several vascular diseases. Conventional blood pressure measurement systems use cuff-based devices to measure the blood pressure, which may be uncomfortable and sometimes burdensome to the subjects. Therefore, in this study, we propose a cuffless blood pressure estimation model based on Monte Carlo simulation (MCS). We propose a heterogeneous finger model for the MCS at wavelengths of 905 nm and 940 nm. After recording the photon intensities from the MCS over a certain range of blood pressure values, the actual photoplethysmography (PPG) signals were used to estimate blood pressure. We used both publicly available and self-made datasets to evaluate the performance of the proposed model. In case of the publicly available dataset for transmission-type MCS, the mean absolute errors are 3.32 ± 6.03 mmHg for systolic blood pressure (SBP), 2.02 ± 2.64 mmHg for diastolic blood pressure (DBP), and 1.76 ± 2.8 mmHg for mean arterial pressure (MAP). The self-made dataset is used for both transmission- and reflection-type MCSs; its mean absolute errors are 2.54 ± 4.24 mmHg for SBP, 1.49 ± 2.82 mmHg for DBP, and 1.51 ± 2.41 mmHg for MAP in the transmission-type case as well as 3.35 ± 5.06 mmHg for SBP, 2.07 ± 2.83 mmHg for DBP, and 2.12 ± 2.83 mmHg for MAP in the reflection-type case. The estimated results of the SBP and DBP satisfy the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) standards and are within Grade A according to the British Hypertension Society (BHS) standards. These results show that the proposed model is efficient for estimating blood pressures using fingertip PPG signals. |
format | Online Article Text |
id | pubmed-8838459 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88384592022-02-13 Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals Haque, Chowdhury Azimul Kwon, Tae-Ho Kim, Ki-Doo Sensors (Basel) Article Blood pressure measurements are one of the most routinely performed medical tests globally. Blood pressure is an important metric since it provides information that can be used to diagnose several vascular diseases. Conventional blood pressure measurement systems use cuff-based devices to measure the blood pressure, which may be uncomfortable and sometimes burdensome to the subjects. Therefore, in this study, we propose a cuffless blood pressure estimation model based on Monte Carlo simulation (MCS). We propose a heterogeneous finger model for the MCS at wavelengths of 905 nm and 940 nm. After recording the photon intensities from the MCS over a certain range of blood pressure values, the actual photoplethysmography (PPG) signals were used to estimate blood pressure. We used both publicly available and self-made datasets to evaluate the performance of the proposed model. In case of the publicly available dataset for transmission-type MCS, the mean absolute errors are 3.32 ± 6.03 mmHg for systolic blood pressure (SBP), 2.02 ± 2.64 mmHg for diastolic blood pressure (DBP), and 1.76 ± 2.8 mmHg for mean arterial pressure (MAP). The self-made dataset is used for both transmission- and reflection-type MCSs; its mean absolute errors are 2.54 ± 4.24 mmHg for SBP, 1.49 ± 2.82 mmHg for DBP, and 1.51 ± 2.41 mmHg for MAP in the transmission-type case as well as 3.35 ± 5.06 mmHg for SBP, 2.07 ± 2.83 mmHg for DBP, and 2.12 ± 2.83 mmHg for MAP in the reflection-type case. The estimated results of the SBP and DBP satisfy the requirements of the Association for the Advancement of Medical Instrumentation (AAMI) standards and are within Grade A according to the British Hypertension Society (BHS) standards. These results show that the proposed model is efficient for estimating blood pressures using fingertip PPG signals. MDPI 2022-02-04 /pmc/articles/PMC8838459/ /pubmed/35161920 http://dx.doi.org/10.3390/s22031175 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Haque, Chowdhury Azimul Kwon, Tae-Ho Kim, Ki-Doo Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals |
title | Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals |
title_full | Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals |
title_fullStr | Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals |
title_full_unstemmed | Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals |
title_short | Cuffless Blood Pressure Estimation Based on Monte Carlo Simulation Using Photoplethysmography Signals |
title_sort | cuffless blood pressure estimation based on monte carlo simulation using photoplethysmography signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8838459/ https://www.ncbi.nlm.nih.gov/pubmed/35161920 http://dx.doi.org/10.3390/s22031175 |
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