Cargando…

Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study

BACKGROUND: Cardiorespiratory fitness (CRF), an important index of physical fitness, is the ability to inhale and provide oxygen to the exercising muscle. However, despite its importance, the current gold standard for measuring CRF is impractical, requiring maximal exercise from the participants. OB...

Descripción completa

Detalles Bibliográficos
Autores principales: Kwon, Soon Bin, Ahn, Joong Woo, Lee, Seung Min, Lee, Joonnyong, Lee, Dongheon, Hong, Jeeyoung, Kim, Hee Chan, Yoon, Hyung-Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592480/
https://www.ncbi.nlm.nih.gov/pubmed/31199336
http://dx.doi.org/10.2196/13327
_version_ 1783429890909929472
author Kwon, Soon Bin
Ahn, Joong Woo
Lee, Seung Min
Lee, Joonnyong
Lee, Dongheon
Hong, Jeeyoung
Kim, Hee Chan
Yoon, Hyung-Jin
author_facet Kwon, Soon Bin
Ahn, Joong Woo
Lee, Seung Min
Lee, Joonnyong
Lee, Dongheon
Hong, Jeeyoung
Kim, Hee Chan
Yoon, Hyung-Jin
author_sort Kwon, Soon Bin
collection PubMed
description BACKGROUND: Cardiorespiratory fitness (CRF), an important index of physical fitness, is the ability to inhale and provide oxygen to the exercising muscle. However, despite its importance, the current gold standard for measuring CRF is impractical, requiring maximal exercise from the participants. OBJECTIVE: This study aimed to develop a convenient and practical estimation model for CRF using data collected from daily life with a wristwatch-type device. METHODS: A total of 191 subjects, aged 20 to 65 years, participated in this study. Maximal oxygen uptake (VO(2) max), a standard measure of CRF, was measured with a maximal exercise test. Heart rate (HR) and physical activity data were collected using a commercial wristwatch-type fitness tracker (Fitbit; Fitbit Charge; Fitbit) for 3 consecutive days. Maximal activity energy expenditure (aEEmax) and slope between HR and physical activity were calculated using a linear regression. A VO(2) max estimation model was built using multiple linear regression with data on age, sex, height, percent body fat, aEEmax, and the slope. The result was validated with 2 different cross-validation methods. RESULTS: aEEmax showed a moderate correlation with VO(2) max (r=0.50). The correlation coefficient for the multiple linear regression model was 0.81, and the SE of estimate (SEE) was 3.518 mL/kg/min. The regression model was cross-validated through the predicted residual error sum of square (PRESS). The PRESS correlation coefficient was 0.79, and the PRESS SEE was 3.667 mL/kg/min. The model was further validated by dividing it into different subgroups and calculating the constant error (CE) where a low CE showed that the model does not significantly overestimate or underestimate VO(2) max. CONCLUSIONS: This study proposes a CRF estimation method using data collected by a wristwatch-type fitness tracker without any specific protocol for a wide range of the population.
format Online
Article
Text
id pubmed-6592480
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-65924802019-07-17 Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study Kwon, Soon Bin Ahn, Joong Woo Lee, Seung Min Lee, Joonnyong Lee, Dongheon Hong, Jeeyoung Kim, Hee Chan Yoon, Hyung-Jin JMIR Mhealth Uhealth Original Paper BACKGROUND: Cardiorespiratory fitness (CRF), an important index of physical fitness, is the ability to inhale and provide oxygen to the exercising muscle. However, despite its importance, the current gold standard for measuring CRF is impractical, requiring maximal exercise from the participants. OBJECTIVE: This study aimed to develop a convenient and practical estimation model for CRF using data collected from daily life with a wristwatch-type device. METHODS: A total of 191 subjects, aged 20 to 65 years, participated in this study. Maximal oxygen uptake (VO(2) max), a standard measure of CRF, was measured with a maximal exercise test. Heart rate (HR) and physical activity data were collected using a commercial wristwatch-type fitness tracker (Fitbit; Fitbit Charge; Fitbit) for 3 consecutive days. Maximal activity energy expenditure (aEEmax) and slope between HR and physical activity were calculated using a linear regression. A VO(2) max estimation model was built using multiple linear regression with data on age, sex, height, percent body fat, aEEmax, and the slope. The result was validated with 2 different cross-validation methods. RESULTS: aEEmax showed a moderate correlation with VO(2) max (r=0.50). The correlation coefficient for the multiple linear regression model was 0.81, and the SE of estimate (SEE) was 3.518 mL/kg/min. The regression model was cross-validated through the predicted residual error sum of square (PRESS). The PRESS correlation coefficient was 0.79, and the PRESS SEE was 3.667 mL/kg/min. The model was further validated by dividing it into different subgroups and calculating the constant error (CE) where a low CE showed that the model does not significantly overestimate or underestimate VO(2) max. CONCLUSIONS: This study proposes a CRF estimation method using data collected by a wristwatch-type fitness tracker without any specific protocol for a wide range of the population. JMIR Publications 2019-06-13 /pmc/articles/PMC6592480/ /pubmed/31199336 http://dx.doi.org/10.2196/13327 Text en ©Soon Bin Kwon, Joong Woo Ahn, Seung Min Lee, Joonnyong Lee, Dongheon Lee, Jeeyoung Hong, Hee Chan Kim, Hyung-Jin Yoon. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 13.06.2019. 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 mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Kwon, Soon Bin
Ahn, Joong Woo
Lee, Seung Min
Lee, Joonnyong
Lee, Dongheon
Hong, Jeeyoung
Kim, Hee Chan
Yoon, Hyung-Jin
Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study
title Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study
title_full Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study
title_fullStr Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study
title_full_unstemmed Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study
title_short Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study
title_sort estimating maximal oxygen uptake from daily activity data measured by a watch-type fitness tracker: cross-sectional study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6592480/
https://www.ncbi.nlm.nih.gov/pubmed/31199336
http://dx.doi.org/10.2196/13327
work_keys_str_mv AT kwonsoonbin estimatingmaximaloxygenuptakefromdailyactivitydatameasuredbyawatchtypefitnesstrackercrosssectionalstudy
AT ahnjoongwoo estimatingmaximaloxygenuptakefromdailyactivitydatameasuredbyawatchtypefitnesstrackercrosssectionalstudy
AT leeseungmin estimatingmaximaloxygenuptakefromdailyactivitydatameasuredbyawatchtypefitnesstrackercrosssectionalstudy
AT leejoonnyong estimatingmaximaloxygenuptakefromdailyactivitydatameasuredbyawatchtypefitnesstrackercrosssectionalstudy
AT leedongheon estimatingmaximaloxygenuptakefromdailyactivitydatameasuredbyawatchtypefitnesstrackercrosssectionalstudy
AT hongjeeyoung estimatingmaximaloxygenuptakefromdailyactivitydatameasuredbyawatchtypefitnesstrackercrosssectionalstudy
AT kimheechan estimatingmaximaloxygenuptakefromdailyactivitydatameasuredbyawatchtypefitnesstrackercrosssectionalstudy
AT yoonhyungjin estimatingmaximaloxygenuptakefromdailyactivitydatameasuredbyawatchtypefitnesstrackercrosssectionalstudy