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=8

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=<p>Maximal oxygen consumption (VO<sub>2</sub>max) reflects aerobic capacity and is crucial for assessing cardiorespiratory fitness and physical activity level. The purpose of this study was to classify and predict the population-based cardiorespiratory fitness based on anthropometric parameters, workload, and steady-state heart rate (HR) of the submaximal exercise test. Five hundred and seventeen participants were recruited into this study. This study initially classified aerobic capacity followed by VO<sub>2</sub>max predicted using an ordinary least squares regression model with measured VO<sub>2</sub>max from a submaximal cycle test as ground truth. Furthermore, we predicted VO<sub>2</sub>max in the age ranges 21–40 and above 40. For the support vector classification model, the test accuracy was 75%. The ordinary least squares regression model showed the coefficient of determination (<italic>R</italic><sup>2</sup>) between measured and predicted VO<sub>2</sub>max was 0.83, mean absolute error (MAE) and root mean square error (RMSE) were 3.12 and 4.24 ml/kg/min, respectively. <italic>R</italic><sup>2</sup> in the age 21–40 and above 40 groups were 0.85 and 0.75, respectively. In conclusion, this study provides a practical protocol for estimating cardiorespiratory fitness of an individual in large populations. An applicable submaximal test for population-based cohorts could evaluate physical activity levels and provide exercise recommendations.</p>