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Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions

BACKGROUND: Currently, many imaging photoplethysmography (IPPG) researches have reported non-contact measurements of physiological parameters, such as heart rate (HR), respiratory rate (RR), etc. However, it is accepted that only HR measurement has been mature for applications, and other estimations...

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Detalles Bibliográficos
Autores principales: Wei, Bing, He, Xuan, Zhang, Chao, Wu, Xiaopei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5439118/
https://www.ncbi.nlm.nih.gov/pubmed/28249595
http://dx.doi.org/10.1186/s12938-016-0300-0
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author Wei, Bing
He, Xuan
Zhang, Chao
Wu, Xiaopei
author_facet Wei, Bing
He, Xuan
Zhang, Chao
Wu, Xiaopei
author_sort Wei, Bing
collection PubMed
description BACKGROUND: Currently, many imaging photoplethysmography (IPPG) researches have reported non-contact measurements of physiological parameters, such as heart rate (HR), respiratory rate (RR), etc. However, it is accepted that only HR measurement has been mature for applications, and other estimations are relatively incapable for reliable applications. Thus, it is worth keeping on persistent studies. Besides, there are some issues commonly involved in these approaches need to be explored further. For example, motion artifact attenuation, an intractable problem, which is being attempted to be resolved by sophisticated video tracking and detection algorithms. METHODS: This paper proposed a blind source separation-based method that could synchronously measure RR and HR in non-contact way. A dual region of interest on facial video image was selected to yield 6-channels Red/Green/Blue signals. By applying Second-Order Blind Identification algorithm to those signals generated above, we obtained 6-channels outputs that contain blood volume pulse (BVP) and respiratory motion artifact. We defined this motion artifact as respiratory signal (RS). For the automatic selections of the RS and BVP among these outputs, we devised a kurtosis-based identification strategy, which guarantees the dynamic RR and HR monitoring available. RESULTS: The experimental results indicated that, the estimation by the proposed method has an impressive performance compared with the measurement of the commercial medical sensors. CONCLUSIONS: The proposed method achieved dynamic measurement of RR and HR, and the extension and revision of it may have the potentials for more physiological signs detection, such as heart rate variability, eye blinking, nose wrinkling, yawn, as well as other muscular movements. Thus, it might provide a promising approach for IPPG-based applications such as emotion computation and fatigue detection, etc. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12938-016-0300-0) contains supplementary material, which is available to authorized users.
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spelling pubmed-54391182017-05-23 Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions Wei, Bing He, Xuan Zhang, Chao Wu, Xiaopei Biomed Eng Online Research BACKGROUND: Currently, many imaging photoplethysmography (IPPG) researches have reported non-contact measurements of physiological parameters, such as heart rate (HR), respiratory rate (RR), etc. However, it is accepted that only HR measurement has been mature for applications, and other estimations are relatively incapable for reliable applications. Thus, it is worth keeping on persistent studies. Besides, there are some issues commonly involved in these approaches need to be explored further. For example, motion artifact attenuation, an intractable problem, which is being attempted to be resolved by sophisticated video tracking and detection algorithms. METHODS: This paper proposed a blind source separation-based method that could synchronously measure RR and HR in non-contact way. A dual region of interest on facial video image was selected to yield 6-channels Red/Green/Blue signals. By applying Second-Order Blind Identification algorithm to those signals generated above, we obtained 6-channels outputs that contain blood volume pulse (BVP) and respiratory motion artifact. We defined this motion artifact as respiratory signal (RS). For the automatic selections of the RS and BVP among these outputs, we devised a kurtosis-based identification strategy, which guarantees the dynamic RR and HR monitoring available. RESULTS: The experimental results indicated that, the estimation by the proposed method has an impressive performance compared with the measurement of the commercial medical sensors. CONCLUSIONS: The proposed method achieved dynamic measurement of RR and HR, and the extension and revision of it may have the potentials for more physiological signs detection, such as heart rate variability, eye blinking, nose wrinkling, yawn, as well as other muscular movements. Thus, it might provide a promising approach for IPPG-based applications such as emotion computation and fatigue detection, etc. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12938-016-0300-0) contains supplementary material, which is available to authorized users. BioMed Central 2017-01-17 /pmc/articles/PMC5439118/ /pubmed/28249595 http://dx.doi.org/10.1186/s12938-016-0300-0 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Wei, Bing
He, Xuan
Zhang, Chao
Wu, Xiaopei
Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions
title Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions
title_full Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions
title_fullStr Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions
title_full_unstemmed Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions
title_short Non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions
title_sort non-contact, synchronous dynamic measurement of respiratory rate and heart rate based on dual sensitive regions
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5439118/
https://www.ncbi.nlm.nih.gov/pubmed/28249595
http://dx.doi.org/10.1186/s12938-016-0300-0
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