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Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health Method

BACKGROUND: Physical inactivity remains the largest risk factor for the development of cardiovascular disease worldwide. Wearable devices have become a popular method of measuring activity-based outcomes and facilitating behavior change to increase cardiorespiratory fitness (CRF) or maximal oxygen c...

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Autores principales: Helgerud, Jan, Haglo, Håvard, Hoff, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9389381/
https://www.ncbi.nlm.nih.gov/pubmed/35925653
http://dx.doi.org/10.2196/38570
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author Helgerud, Jan
Haglo, Håvard
Hoff, Jan
author_facet Helgerud, Jan
Haglo, Håvard
Hoff, Jan
author_sort Helgerud, Jan
collection PubMed
description BACKGROUND: Physical inactivity remains the largest risk factor for the development of cardiovascular disease worldwide. Wearable devices have become a popular method of measuring activity-based outcomes and facilitating behavior change to increase cardiorespiratory fitness (CRF) or maximal oxygen consumption (VO(2max)) and reduce weight. However, it is critical to determine their accuracy in measuring these variables. OBJECTIVE: This study aimed to determine the accuracy of using a smartphone and the application Myworkout GO for submaximal prediction of VO(2max). METHODS: Participants included 162 healthy volunteers: 58 women and 104 men (17-73 years old). The study consisted of 3 experimental tests randomized to 3 separate days. One-day VO(2max) was assessed with Metamax II, with the participant walking or running on the treadmill. On the 2 other days, the application Myworkout GO used standardized high aerobic intensity interval training (HIIT) on the treadmill to predict VO(2max). RESULTS: There were no significant differences between directly measured VO(2max) (mean 49, SD 14 mL/kg/min) compared with the VO(2max) predicted by Myworkout GO (mean 50, SD 14 mL/kg/min). The direct and predicted VO(2max) values were highly correlated, with an R(2) of 0.97 (P<.001) and standard error of the estimate (SEE) of 2.2 mL/kg/min, with no sex differences. CONCLUSIONS: Myworkout GO accurately calculated VO(2max), with an SEE of 4.5% in the total group. The submaximal HIIT session (4 x 4 minutes) incorporated in the application was tolerated well by the participants. We present health care providers and their patients with a more accurate and practical version of health risk estimation. This might increase physical activity and improve exercise habits in the general population.
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spelling pubmed-93893812022-08-20 Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health Method Helgerud, Jan Haglo, Håvard Hoff, Jan JMIR Cardio Original Paper BACKGROUND: Physical inactivity remains the largest risk factor for the development of cardiovascular disease worldwide. Wearable devices have become a popular method of measuring activity-based outcomes and facilitating behavior change to increase cardiorespiratory fitness (CRF) or maximal oxygen consumption (VO(2max)) and reduce weight. However, it is critical to determine their accuracy in measuring these variables. OBJECTIVE: This study aimed to determine the accuracy of using a smartphone and the application Myworkout GO for submaximal prediction of VO(2max). METHODS: Participants included 162 healthy volunteers: 58 women and 104 men (17-73 years old). The study consisted of 3 experimental tests randomized to 3 separate days. One-day VO(2max) was assessed with Metamax II, with the participant walking or running on the treadmill. On the 2 other days, the application Myworkout GO used standardized high aerobic intensity interval training (HIIT) on the treadmill to predict VO(2max). RESULTS: There were no significant differences between directly measured VO(2max) (mean 49, SD 14 mL/kg/min) compared with the VO(2max) predicted by Myworkout GO (mean 50, SD 14 mL/kg/min). The direct and predicted VO(2max) values were highly correlated, with an R(2) of 0.97 (P<.001) and standard error of the estimate (SEE) of 2.2 mL/kg/min, with no sex differences. CONCLUSIONS: Myworkout GO accurately calculated VO(2max), with an SEE of 4.5% in the total group. The submaximal HIIT session (4 x 4 minutes) incorporated in the application was tolerated well by the participants. We present health care providers and their patients with a more accurate and practical version of health risk estimation. This might increase physical activity and improve exercise habits in the general population. JMIR Publications 2022-08-04 /pmc/articles/PMC9389381/ /pubmed/35925653 http://dx.doi.org/10.2196/38570 Text en ©Jan Helgerud, Håvard Haglo, Jan Hoff. Originally published in JMIR Cardio (https://cardio.jmir.org), 04.08.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Cardio, is properly cited. The complete bibliographic information, a link to the original publication on https://cardio.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Helgerud, Jan
Haglo, Håvard
Hoff, Jan
Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health Method
title Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health Method
title_full Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health Method
title_fullStr Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health Method
title_full_unstemmed Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health Method
title_short Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health Method
title_sort prediction of vo2max from submaximal exercise using the smartphone application myworkout go: validation study of a digital health method
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9389381/
https://www.ncbi.nlm.nih.gov/pubmed/35925653
http://dx.doi.org/10.2196/38570
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