AUTHOR=Xiang Liangliang , Deng Kaili , Mei Qichang , Gao Zixiang , Yang Tao , Wang Alan , Fernandez Justin , Gu Yaodong 

TITLE=Population and Age-Based Cardiorespiratory Fitness Level Investigation and Automatic Prediction

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=Volume 8 - 2021

YEAR=2022

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2021.758589

DOI=10.3389/fcvm.2021.758589

ISSN=2297-055X

ABSTRACT=Maximal oxygen consumption (VO2max) reflects aerobic capacity and is crucial for assessing cardiorespiratory fitness and physical activity level. The purpose of the present study was to classify and predict the population-based cardiorespiratory fitness based on the anthropometric parameters, workload, and steady-state heart rate (HR) of the submaximal exercise test. 517 participants were recruited into this study. This study initially classified the aerobic capacity, then VO2max was predicted using the ordinary least squares regression model with measured VO2max from submaximal cycle test as ground-true value. Furthermore, we predicted VO2max in the age 21-40 and above 40 groups. For the support vector classification model, the test accuracy was 74%. The ordinary least squares regression model showed the Pearson correlation coefficient between measured and predicted VO2max was 0.81, mean absolute error (MAE), and root mean square error (RMSE) were 3.31 ml/kg/min and 4.54 ml/kg/min. Pearson correlation coefficient in the age 21-40 and above 40 groups were R2=0.88 and R2=0.70. In conclusion, this study provides a practical protocol for estimating the individual’s cardiorespiratory fitness in large populations. An applicable submaximal test for population-based cohorts could evaluate physical activity levels and provide exercise recommendations.