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Unobtrusive Estimation of Cardiorespiratory Fitness with Daily Activity in Healthy Young Men.

Authors
  • Ahn, Joong Woo1
  • Hwang, Se Hee2
  • Yoon, Chiyul1
  • Lee, Joonnyong1
  • Kim, Hee Chan3
  • Yoon, Hyung Jin4
  • 1 Interdisciplinary Program in Bioengineering, Seoul National University, Seoul, Korea. , (North Korea)
  • 2 Research Institute, National Medical Center, Seoul, Korea. , (North Korea)
  • 3 Department of Biomedical Engineering, Medical Research Center, Seoul National University College of Medicine, Seoul, Korea. , (North Korea)
  • 4 Department of Biomedical Engineering, Medical Research Center, Seoul National University College of Medicine, Seoul, Korea. [email protected] , (North Korea)
Type
Published Article
Journal
Journal of Korean medical science
Publication Date
Dec 01, 2017
Volume
32
Issue
12
Pages
1947–1952
Identifiers
DOI: 10.3346/jkms.2017.32.12.1947
PMID: 29115075
Source
Medline
Keywords
License
Unknown

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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