J Korean Med Sci.  2017 Dec;32(12):1947-1952. 10.3346/jkms.2017.32.12.1947.

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

• Ahn JW
• Hwang SH
• Yoon C
• Lee J
• Kim HC
• Yoon HJ

• KMID: 2396370
• DOI: http://doi.org/10.3346/jkms.2017.32.12.1947

Abstract

Despite the importance of cardiorespiratory fitness, no practical method exists to estimate maximal oxygen consumption (VOâ‚‚max) without a specific exercise protocol. We developed an estimation model of VOâ‚‚max, 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 VOâ‚‚max 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 VOâ‚‚max 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 VOâ‚‚max and the measured VOâ‚‚max were identified in both groups, with a 15-hour recording being sufficient to produce a highly accurate VOâ‚‚max estimate. Additional recording time did not significantly improve the accuracy of the estimation. Our VOâ‚‚max estimation method provides a robust alternative to traditional approaches while only requiring minimal data acquisition time in daily life.

Keyword

Cardiorespiratory Fitness; Oxygen Consumption; Energy Expenditure; Maximal Activity Energy Expenditure

MeSH Terms

Acceleration
Body Weight
Electrocardiography
Energy Metabolism
Exercise Test
Heart Rate
Humans
Linear Models
Male
Methods
Motor Activity
Oxygen Consumption

Figure

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  Fig. 1 Signal processing procedure. (A) aEE (in units of J/min), and HR (in units of beats per minute) for one participant. HR data is shown as a thick line and the increasing HR period (at least 4 minutes) is shown in the shadowed region under the smoothed HR curve. (B) Scatter plot of the aEE and HR of the same participant. A simple linear regression was performed to obtain aEEmax at a maximal HR (220 − age). aEE = activity energy expenditure, HR = heart rate, aEEmax = maximal activity energy expenditure.

• 

  Fig. 2 Change of correlation coefficient between aEEmax and measured VO2max. The correlation coefficient was 0.81 at 900 minutes of HR and aEE data analysis to calculate aEEmax. The correlation coefficient fluctuated but did not drastically increase when longer periods were used. aEEmax = maximal activity energy expenditure, VO2max = maximal oxygen consumption, aEE = activity energy expenditure, HR = heart rate.

• 

  Fig. 3 The correlation between the estimated and measured VO2max. (A) Correlation between the estimated and measured VO2max value of all participants. The thin line is the identity line of the measured and estimated VO2max. (B) Bland-Altman plot (estimated-measured VO2max, n = 24). The solid line represents the mean value, and the dotted line represents the 1.96 SD (95% limit of agreement). With the exception of one participant, the data was randomly distributed among the 1.96 SD range. VO2max = maximal oxygen consumption, SD = standard deviation

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