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Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running

Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of thi...

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Autores principales: Prigent, Gaëlle, Aminian, Kamiar, Rodrigues, Tiago, Vesin, Jean-Marc, Millet, Grégoire P., Falbriard, Mathieu, Meyer, Frédéric, Paraschiv-Ionescu, Anisoara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8402314/
https://www.ncbi.nlm.nih.gov/pubmed/34451093
http://dx.doi.org/10.3390/s21165651
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author Prigent, Gaëlle
Aminian, Kamiar
Rodrigues, Tiago
Vesin, Jean-Marc
Millet, Grégoire P.
Falbriard, Mathieu
Meyer, Frédéric
Paraschiv-Ionescu, Anisoara
author_facet Prigent, Gaëlle
Aminian, Kamiar
Rodrigues, Tiago
Vesin, Jean-Marc
Millet, Grégoire P.
Falbriard, Mathieu
Meyer, Frédéric
Paraschiv-Ionescu, Anisoara
author_sort Prigent, Gaëlle
collection PubMed
description Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying/validating our approaches during in-field endurance running in the context of fatigue assessment.
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spelling pubmed-84023142021-08-29 Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running Prigent, Gaëlle Aminian, Kamiar Rodrigues, Tiago Vesin, Jean-Marc Millet, Grégoire P. Falbriard, Mathieu Meyer, Frédéric Paraschiv-Ionescu, Anisoara Sensors (Basel) Article Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying/validating our approaches during in-field endurance running in the context of fatigue assessment. MDPI 2021-08-22 /pmc/articles/PMC8402314/ /pubmed/34451093 http://dx.doi.org/10.3390/s21165651 Text en © 2021 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
Prigent, Gaëlle
Aminian, Kamiar
Rodrigues, Tiago
Vesin, Jean-Marc
Millet, Grégoire P.
Falbriard, Mathieu
Meyer, Frédéric
Paraschiv-Ionescu, Anisoara
Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running
title Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running
title_full Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running
title_fullStr Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running
title_full_unstemmed Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running
title_short Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running
title_sort indirect estimation of breathing rate from heart rate monitoring system during running
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8402314/
https://www.ncbi.nlm.nih.gov/pubmed/34451093
http://dx.doi.org/10.3390/s21165651
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