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Estimation of Health-Related Physical Fitness (HRPF) Levels of the General Public Using Artificial Neural Network with the National Fitness Award (NFA) Datasets

Authors :
Sung-Woo Kim
Hoeryong Jung
Seunghun Lee
Sang-Hun Lee
Young-Eun Song
Hyeon-Seong Ju
Seung-Wan Kang
Kiwon Lim
Hun-Young Park
Source :
International Journal of Environmental Research and Public Health, Vol 18, Iss 10391, p 10391 (2021), International Journal of Environmental Research and Public Health, Volume 18, Issue 19
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

Estimation of health-related physical fitness (HRPF) levels of individuals is indispensable for providing personalized training programs in smart fitness services. In this study, we propose an artificial neural network (ANN)-based estimation model to predict HRPF levels of the general public using simple affordable physical information. The model is designed to use seven inputs of personal physical information, including age, gender, height, weight, percent body fat, waist circumference, and body mass index (BMI), to estimate levels of muscle strength, flexibility, maximum rate of oxygen consumption (VO2max), and muscular endurance. HRPF data (197,719 sets) gathered from the National Fitness Award dataset are used for training (70%) and validation (30%) of the model. In-depth analysis of the model’s estimation accuracy is conducted to derive optimal estimation accuracy. This included input/output correlation, hidden layer structures, data standardization, and outlier removals. The performance of the model is evaluated by comparing the estimation accuracy with that of a multiple linear regression (MLR) model. The results demonstrate that the proposed model achieved up to 10.06% and 30.53% improvement in terms of R2 and SEE, respectively, compared to the MLR model and provides reliable estimation of HRPF levels acceptable to smart fitness applications.

Details

Language :
English
ISSN :
16617827 and 16604601
Volume :
18
Issue :
10391
Database :
OpenAIRE
Journal :
International Journal of Environmental Research and Public Health
Accession number :
edsair.doi.dedup.....5e4190d70b65cc17143932220855e7df