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Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement
Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearab...
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/PMC8946827/ https://www.ncbi.nlm.nih.gov/pubmed/35323420 http://dx.doi.org/10.3390/bios12030150 |
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author | Wang, Ting-Wei Syu, Jhen-Yang Chu, Hsiao-Wei Sung, Yen-Ling Chou, Lin Escott, Endian Escott, Olivia Lin, Ting-Tse Lin, Shien-Fong |
author_facet | Wang, Ting-Wei Syu, Jhen-Yang Chu, Hsiao-Wei Sung, Yen-Ling Chou, Lin Escott, Endian Escott, Olivia Lin, Ting-Tse Lin, Shien-Fong |
author_sort | Wang, Ting-Wei |
collection | PubMed |
description | Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearable applications. Recently, wearable and smart health electronics have become significant for next-generation personalized healthcare progress. This study proposes an intelligent single-channel bio-impedance system for personalized BP monitoring. Compared to the PTT-based methods, the proposed sensing configuration greatly reduces the hardware complexity, which is beneficial for wearable applications. Most of all, the proposed system can extract the significant BP features hidden from the measured bio-impedance signals by an ultra-lightweight AI algorithm, implemented to further establish a tailored BP model for personalized healthcare. In the human trial, the proposed system demonstrates the BP accuracy in terms of the mean error (ME) and the mean absolute error (MAE) within 1.7 ± 3.4 mmHg and 2.7 ± 2.6 mmHg, respectively, which agrees with the criteria of the Association for the Advancement of Medical Instrumentation (AAMI). In conclusion, this work presents a proof-of-concept for an AI-based single-channel bio-impedance BP system. The new wearable smart system is expected to accelerate the artificial intelligence of things (AIoT) technology for personalized BP healthcare in the future. |
format | Online Article Text |
id | pubmed-8946827 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-89468272022-03-25 Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement Wang, Ting-Wei Syu, Jhen-Yang Chu, Hsiao-Wei Sung, Yen-Ling Chou, Lin Escott, Endian Escott, Olivia Lin, Ting-Tse Lin, Shien-Fong Biosensors (Basel) Article Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearable applications. Recently, wearable and smart health electronics have become significant for next-generation personalized healthcare progress. This study proposes an intelligent single-channel bio-impedance system for personalized BP monitoring. Compared to the PTT-based methods, the proposed sensing configuration greatly reduces the hardware complexity, which is beneficial for wearable applications. Most of all, the proposed system can extract the significant BP features hidden from the measured bio-impedance signals by an ultra-lightweight AI algorithm, implemented to further establish a tailored BP model for personalized healthcare. In the human trial, the proposed system demonstrates the BP accuracy in terms of the mean error (ME) and the mean absolute error (MAE) within 1.7 ± 3.4 mmHg and 2.7 ± 2.6 mmHg, respectively, which agrees with the criteria of the Association for the Advancement of Medical Instrumentation (AAMI). In conclusion, this work presents a proof-of-concept for an AI-based single-channel bio-impedance BP system. The new wearable smart system is expected to accelerate the artificial intelligence of things (AIoT) technology for personalized BP healthcare in the future. MDPI 2022-02-28 /pmc/articles/PMC8946827/ /pubmed/35323420 http://dx.doi.org/10.3390/bios12030150 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 Wang, Ting-Wei Syu, Jhen-Yang Chu, Hsiao-Wei Sung, Yen-Ling Chou, Lin Escott, Endian Escott, Olivia Lin, Ting-Tse Lin, Shien-Fong Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement |
title | Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement |
title_full | Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement |
title_fullStr | Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement |
title_full_unstemmed | Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement |
title_short | Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement |
title_sort | intelligent bio-impedance system for personalized continuous blood pressure measurement |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8946827/ https://www.ncbi.nlm.nih.gov/pubmed/35323420 http://dx.doi.org/10.3390/bios12030150 |
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