ArticleJournal of Korean medical science2017
Unobtrusive Estimation of Cardiorespiratory Fitness with Daily Activity in Healthy Young Men.
Article in Journal of Korean medical science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Exploiting Unsupervised Free-Living Data for Cardiorespiratory Fitness Estimation: Systematic Review and Meta-Analysis.JMIR mHealth and uHealth · 2026Pooled it
- Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study.JMIR mHealth and uHealth · 2019Article
- Data fusion of body-worn accelerometers and heart rate to predict VO2max during submaximal running.PloS one · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the importance of cardiorespiratory fitness, no practical method exists to estimate maximal oxygen consumption (VO₂max) without a specific exercise protocol. We developed an estimation model of VO₂max, using maximal activity energy expenditure (aEEmax) as a new feature to represent the level of physical activity. Electrocardiogram (ECG) and acceleration data were recorded for 4 days in 24 healthy young men, and reference VO₂max levels were measured using the maximal exercise test. aEE was calculated using the measured acceleration data and body weight, while heart rate (HR) was extracted from the ECG signal. aEEmax was obtained using linear regression, with aEE and HR as input parameters. The VO₂max was estimated from the aEEmax using multiple linear regression modeling in the training group (n = 16) and was verified in the test group (n = 8). High correlations between the estimated VO₂max and the measured VO₂max were identified in both groups, with a 15-hour recording being sufficient to produce a highly accurate VO₂max estimate. Additional recording time did not significantly improve the accuracy of the estimation. Our VO₂max estimation method provides a robust alternative to traditional approaches while only requiring minimal data acquisition time in daily life.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.