Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health Method
BackgroundPhysical 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 (CR...
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| Format: | Article |
| Language: | English |
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JMIR Publications
2022-08-01
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| Series: | JMIR Cardio |
| Online Access: | https://cardio.jmir.org/2022/2/e38570 |
| _version_ | 1797734867669090304 |
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| author | Jan Helgerud Håvard Haglo Jan Hoff |
| author_facet | Jan Helgerud Håvard Haglo Jan Hoff |
| author_sort | Jan Helgerud |
| collection | DOAJ |
| description |
BackgroundPhysical 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 (VO2max) and reduce weight. However, it is critical to determine their accuracy in measuring these variables.
ObjectiveThis study aimed to determine the accuracy of using a smartphone and the application Myworkout GO for submaximal prediction of VO2max.
MethodsParticipants 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 VO2max 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 VO2max.
ResultsThere were no significant differences between directly measured VO2max (mean 49, SD 14 mL/kg/min) compared with the VO2max predicted by Myworkout GO (mean 50, SD 14 mL/kg/min). The direct and predicted VO2max values were highly correlated, with an R2 of 0.97 (P<.001) and standard error of the estimate (SEE) of 2.2 mL/kg/min, with no sex differences.
ConclusionsMyworkout GO accurately calculated VO2max, 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. |
| first_indexed | 2024-03-12T12:50:45Z |
| format | Article |
| id | doaj.art-9e170ef8d4c94276a82a34b052f3f81b |
| institution | Directory Open Access Journal |
| issn | 2561-1011 |
| language | English |
| last_indexed | 2024-03-12T12:50:45Z |
| publishDate | 2022-08-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Cardio |
| spelling | doaj.art-9e170ef8d4c94276a82a34b052f3f81b2023-08-28T22:48:59ZengJMIR PublicationsJMIR Cardio2561-10112022-08-0162e3857010.2196/38570Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health MethodJan Helgerudhttps://orcid.org/0000-0002-7796-5594Håvard Haglohttps://orcid.org/0000-0001-7147-4463Jan Hoffhttps://orcid.org/0000-0002-8432-7304 BackgroundPhysical 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 (VO2max) and reduce weight. However, it is critical to determine their accuracy in measuring these variables. ObjectiveThis study aimed to determine the accuracy of using a smartphone and the application Myworkout GO for submaximal prediction of VO2max. MethodsParticipants 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 VO2max 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 VO2max. ResultsThere were no significant differences between directly measured VO2max (mean 49, SD 14 mL/kg/min) compared with the VO2max predicted by Myworkout GO (mean 50, SD 14 mL/kg/min). The direct and predicted VO2max values were highly correlated, with an R2 of 0.97 (P<.001) and standard error of the estimate (SEE) of 2.2 mL/kg/min, with no sex differences. ConclusionsMyworkout GO accurately calculated VO2max, 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.https://cardio.jmir.org/2022/2/e38570 |
| spellingShingle | Jan Helgerud Håvard Haglo Jan Hoff Prediction of VO2max From Submaximal Exercise Using the Smartphone Application Myworkout GO: Validation Study of a Digital Health Method JMIR Cardio |
| 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 |
| url | https://cardio.jmir.org/2022/2/e38570 |
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