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Estimation of Cardiorespiratory fitness using a using a chest mounted accelerometer

 : Cardiorespiratory fitness expressed as maximal oxygen consumption (V̇O(2 max)) is a strong predictor of cardiovascular health. However, quantification of cardiorespiratory fitness by cardiopulmonary exercise (CPX) assessment is complex and costly and therefore not suitable in most clinical settin...

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Autores principales: Schmidt, S E, Hansen, M T, Roemer, T, Soegaard, P, Helge, J W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9779770/
http://dx.doi.org/10.1093/ehjdh/ztac076.2769
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author Schmidt, S E
Hansen, M T
Roemer, T
Soegaard, P
Helge, J W
author_facet Schmidt, S E
Hansen, M T
Roemer, T
Soegaard, P
Helge, J W
author_sort Schmidt, S E
collection PubMed
description  : Cardiorespiratory fitness expressed as maximal oxygen consumption (V̇O(2 max)) is a strong predictor of cardiovascular health. However, quantification of cardiorespiratory fitness by cardiopulmonary exercise (CPX) assessment is complex and costly and therefore not suitable in most clinical settings. In the current study we develop and validate an algorithm for estimation of V̇O(2 max) using seismocardiography (SCG-V̇O(2 max)). SCG is measurement of precordial vibrations using an accelerometer. METHODS: SCG recordings and results from ergometer CPX testing of V̇O(2 max) in 300 subjects from six clinical studies were combined in a database. 83 subjects underwent repeated measurements sessions across several days. SCG was obtained using a sensitive accelerometer, located on the lower sternum at the Xiphoid protrusion and subjects were placed in a supine position. 5 subjects were excluded due to cardiovascular disease, or missing data. A machine learning algorithm was devolved for estimation of V̇O(2 max) in a training set including 221 subjects. The remaining 74 subjects were included in a test set for validation. Correlation and accuracy between SCG-V̇O(2 max) and ergometer CPX V̇O(2 max) assessed and day to day variation was assessed in subjects who underwent multiple ergometer CPX sessions. RESULTS: In 144 recordings from 74 test set subjects SCG-V̇O(2 max) was 45.0±9.3 ml/min/kg which was comparable to the ergometer CPX V̇O(2 max) at 44.3±10.1 ml/min/kg (p=0.09) and correlation between ergometer CPX V̇O(2 max) and SCG-V̇O(2 max) was r=0.875. Mean average percentage error was 8.7%. Day to day variation measured as the within-subjects-standard-deviation was 1.2 ml/min/kg for SCG-V̇O(2 max) and 1.7 ml/min/kg for ergometer CPX. CONCLUSIONS: SCG based estimation of VV̇O(2 max) is a novel, low cost, easy to use and accurate estimation method of CRF with a high level of reproducibility. SCG-V̇O(2 max) can potentially facilitate that cardiorespiratory fitness becomes an integrated part of modern health assessment. FUNDING ACKNOWLEDGEMENT: Type of funding sources: Private company. Main funding source(s): VentriJect A/S DK
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spelling pubmed-97797702023-01-27 Estimation of Cardiorespiratory fitness using a using a chest mounted accelerometer Schmidt, S E Hansen, M T Roemer, T Soegaard, P Helge, J W Eur Heart J Digit Health Abstracts  : Cardiorespiratory fitness expressed as maximal oxygen consumption (V̇O(2 max)) is a strong predictor of cardiovascular health. However, quantification of cardiorespiratory fitness by cardiopulmonary exercise (CPX) assessment is complex and costly and therefore not suitable in most clinical settings. In the current study we develop and validate an algorithm for estimation of V̇O(2 max) using seismocardiography (SCG-V̇O(2 max)). SCG is measurement of precordial vibrations using an accelerometer. METHODS: SCG recordings and results from ergometer CPX testing of V̇O(2 max) in 300 subjects from six clinical studies were combined in a database. 83 subjects underwent repeated measurements sessions across several days. SCG was obtained using a sensitive accelerometer, located on the lower sternum at the Xiphoid protrusion and subjects were placed in a supine position. 5 subjects were excluded due to cardiovascular disease, or missing data. A machine learning algorithm was devolved for estimation of V̇O(2 max) in a training set including 221 subjects. The remaining 74 subjects were included in a test set for validation. Correlation and accuracy between SCG-V̇O(2 max) and ergometer CPX V̇O(2 max) assessed and day to day variation was assessed in subjects who underwent multiple ergometer CPX sessions. RESULTS: In 144 recordings from 74 test set subjects SCG-V̇O(2 max) was 45.0±9.3 ml/min/kg which was comparable to the ergometer CPX V̇O(2 max) at 44.3±10.1 ml/min/kg (p=0.09) and correlation between ergometer CPX V̇O(2 max) and SCG-V̇O(2 max) was r=0.875. Mean average percentage error was 8.7%. Day to day variation measured as the within-subjects-standard-deviation was 1.2 ml/min/kg for SCG-V̇O(2 max) and 1.7 ml/min/kg for ergometer CPX. CONCLUSIONS: SCG based estimation of VV̇O(2 max) is a novel, low cost, easy to use and accurate estimation method of CRF with a high level of reproducibility. SCG-V̇O(2 max) can potentially facilitate that cardiorespiratory fitness becomes an integrated part of modern health assessment. FUNDING ACKNOWLEDGEMENT: Type of funding sources: Private company. Main funding source(s): VentriJect A/S DK Oxford University Press 2022-12-22 /pmc/articles/PMC9779770/ http://dx.doi.org/10.1093/ehjdh/ztac076.2769 Text en Reproduced from: European Heart Journal, Volume 43, Issue Supplement_2, October 2022, ehac544.2769, https://doi.org/10.1093/eurheartj/ehac544.2769 by permission of Oxford University Press on behalf of the European Society of Cardiology. The opinions expressed in the Journal item reproduced as this reprint are those of the authors and contributors, and do not necessarily reflect those of the European Society of Cardiology, the editors, the editorial board, Oxford University Press or the organization to which the authors are affiliated. The mention of trade names, commercial products or organizations, and the inclusion of advertisements in this reprint do not imply endorsement by the Journal, the editors, the editorial board, Oxford University Press or the organization to which the authors are affiliated. The editors and publishers have taken all reasonable precautions to verify drug names and doses, the results of experimental work and clinical findings published in the Journal. The ultimate responsibility for the use and dosage of drugs mentioned in this reprint and in interpretation of published material lies with the medical practitioner, and the editors and publisher cannot accept liability for damages arising from any error or omissions in the Journal or in this reprint. Please inform the editors of any errors. © The Author(s) 2022. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Abstracts
Schmidt, S E
Hansen, M T
Roemer, T
Soegaard, P
Helge, J W
Estimation of Cardiorespiratory fitness using a using a chest mounted accelerometer
title Estimation of Cardiorespiratory fitness using a using a chest mounted accelerometer
title_full Estimation of Cardiorespiratory fitness using a using a chest mounted accelerometer
title_fullStr Estimation of Cardiorespiratory fitness using a using a chest mounted accelerometer
title_full_unstemmed Estimation of Cardiorespiratory fitness using a using a chest mounted accelerometer
title_short Estimation of Cardiorespiratory fitness using a using a chest mounted accelerometer
title_sort estimation of cardiorespiratory fitness using a using a chest mounted accelerometer
topic Abstracts
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9779770/
http://dx.doi.org/10.1093/ehjdh/ztac076.2769
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