Artificial Neural Network-Based Model for Evaluating Maximum Oxygen Uptake from the Incremental Squatting Test in Young People

Background: Currently, there are two methods for testing maximal oxygen uptake: the direct and indirect methods, but both have certain requirements for testing equipment, site, and personnel. There is a lack of a convenient and effective method for testing maximum oxygen uptake (VO2max). With the development of artificial neural network (ANN), a solution to this gap is provided. Objective: The goal of this study was to design a method to evaluate the cardiopulmonary function of young people and verify its feasibility and reliability. Methods: The incremental squat test (IST) and Young Men’s Christian Association (YMCA) test were designed with 196 subjects (97 males and 99 females). The back propagation (BP) neural network was used to construct the model of VO2max by recording and analyzing squatting times, height, weight, gender, age, leg length, Manou Riers Skelic index (MRSI), and VO2max. Results: Three hidden layers and 65 nodes were employed in the BP neural network. Each hidden layer contained 19 nodes. Other parameters of this network were 0.01, 0.9, and 2000 for the learning rate, momentum, and iterations, respectively. The difference between the measurements and predictions was not significant (p > 0.05), and the correlation between them was extremely strong (r = 0.98, p < 0.01). Conclusions: We conclude that the model constructed using the BP neural network is accurate, and the IST is feasible for predicting VO2max. This method can be used as a substitute for other cardiopulmonary fitness test protocols in cases of insufficient venues and equipment. thereby preventing health complications. In subsequent studies, the sample size should be expanded, and separate prediction models should be developed for different genders.

cardiorespiratory endurance assessment; indirect; maximum oxygen uptake; incremental squatting test; BP neural network

[1] Furian M, Flueck D, Latshang TD, Scheiwiller PM, Segitz SD, Mueller-Mottet S, et al. Exercise performance and symptoms in lowlanders with COPD ascending to moderate altitude: ran-domized trial. International Journal of Chronic Obstructive Pul-monary Disease. 2018; 13: 3529–3538.

[2] Kunutsor SK, Laukkanen T, Laukkanen JA. Cardiorespiratory Fitness is Associated with Reduced Risk of Respiratory Diseases in Middle-Aged Caucasian Men: a Long-Term Prospective Co-hort Study. Lung. 2017; 195: 607–611.

[3] León-Ariza HH, Botero-Rosas DA, Zea-Robles AC. Heart Rate Variability and Body Composition as Vo2max Determinants. Re-vista Brasileira De Medicina do Esporte. 2017; 23: 317–321.

[4] Toulouse L, Baquet G, Heyman E, Pezé T, Berthoin S, Schill A, et al. Respiratory responses and rating of perceived exertion of severely obese adolescents during continuous and intermittent graded walking protocols: Application to cardiorespiratory field tests. Journal of Sports Sciences. 2020; 38: 1009–1017.

[5] Kokkinos P, Kaminsky LA, Arena R, Zhang J, Franklin B, Kraus W, et al. New Equations for Predicting Maximum Oxygen Up-take in Patients with Heart Failure. The American Journal of Cardiology. 2020; 128: 7–11.

[6] Policarpo Barbosa F, Silva PE, Guimarães AC, Pernambuco CS, Dantas EH. Prediction of maximum oxygen uptake through in-cremental exercise testing using ventilometry: a cross-sectional study. Brazilian Journal of Physical Therapy. 2020; 24: 365–372.

[7] Cooper DM. Rethinking V̇ o2max: right problem, wrong solution (Letter to the Editor regarding Poole and Jones’ “Measurement of the maximum oxygen uptake V̇ o2max: V̇ o2peak is no longer acceptable”). Journal of Applied Physiology. 2017; 123: 498.

[8] Rusdiana A. Analysis Differences of Vo2max between Direct and Indirect Measurement in Badminton, Bicycle Racing and Rowing. International Journal of Applied Exercise Physiology. 2020; 9: 162–170.

[9] Sun ZW, Zhang B, Ma YP. ‘Comparative and Validation Study on Foreign Classic Estimation Equations about VO2max in 1- mile Jog’, Proceedings of the International Symposium on Common Development of Sports and Modern Society. Suzhou, China, F Dec 27–28, 2014. Science & Research Central Ltd: Newark. 2014.

[10] Guo H, Wang Z, Zhang Y. Predicting Vo2max from a 6-minute Stairs Climbing and Descending Test (6MSCDT). Medicine & Science in Sports & Exercise. 2016; 48: 93.

[11] Hansen D, Jacobs N, Thijs H, Dendale P, Claes N. Validation of a single-stage fixed-rate step test for the prediction of max-imal oxygen uptake in healthy adults. Clinical Physiology and Functional Imaging. 2016; 36: 401–406.

[12] Jalili M, Nazem F, Sazvar A, Ranjbar K. Prediction of Maximal Oxygen Uptake by Six-Minute Walk Test and Body Mass Index in Healthy Boys. The Journal of Pediatrics. 2018; 200: 155–159.

[13] Magee MK, White JB, Merrigan JJ, Jones MT. Does the Mul-tistage 20-m Shuttle Run Test Accurately Predict VO2max in NCAA Division I Women Collegiate Field Hockey Athletes?Sports. 2021; 9: 75.

[14] Plasqui G, Westerterp KR. Accelerometry and heart rate as a measure of physical fitness: cross-validation. Medicine and Sci-ence in Sports and Exercise. 2006; 38: 1510–1514.

[15] Aandstad A, Holme I, Berntsen S, Anderssen SA. Validity and Reliability of the 20 Meter Shuttle Run Test in Military Person-nel. Military Medicine. 2011; 176: 513–518.

[16] Higino WP, Sorroche ADS, de Mattos Falqueiro PG, Suzuki Lima YC, Higa CL. Determination of Aerobic Performance in Youth Soccer Players: Effect of Direct and Indirect Methods. Journal of Human Kinetics. 2017; 56: 109–118.

[17] Santos-Silva PR, Fonseca AJ, Castro AW, Greve JM, Hernan-dez AJ. Reproducibility of maximum aerobic power (VO2max) among soccer players using a modified Heck protocol. Clinics. 2007; 62: 391–396.

[18] Takao K, Ueno H, Hamaguchi K, Isaka T. Comparison of aero-bic profiles between the field-based 20 m-shuttle run test and the laboratory-based bike ergometer test in runners. Gazzetta Med-ica Italiana Archivio per Le Scienze Mediche. 2021; 180: 59–64.

[19] Canino M C , Cohen B S , Redmond J E , et al. The Relationship Between Soldier Performance on the Two-Mile Run and the 20-m Shuttle Run Test[J]. Military Medicine(5-6):5-6.

[20] Chen H, Liu C. Research on Knee Injuries in College Football Training Based on Artificial Neural Network. 2020 IEEE Con-ference on Telecommunications, Optics and Computer Science (TOCS). 2020; 35–37.

[21] Drywień M, Górnicki K, Górnicka M. Application of Artifi-cial Neural Network to Somatotype Determination. Applied Sci-ences. 2021; 11: 1365.

[22] Hayakawa Y, Oonuma T, Kobayashi H, Takahashi A, Chiba S, Fujiki NM. Feature Extraction of Video Using Artificial Neu-ral Network. International Journal of Cognitive Informatics and Natural Intelligence. 2017; 11: 16.

[23] Liankun J, Yangyong. Hybrid Neural Network Based Risk As-sessment Method for Large Scale Sports Events. 2014 Fifth In-ternational Conference on Intelligent Systems Design and Engi-neering Applications. 2014; 524–527.

[24] Tümer AE, Koçer S. Prediction of team league’s rankings in vol-leyball by artificial neural network method. International Journal of Performance Analysis in Sport. 2017; 17: 202–211.

[25] Saikia H, Bhattacharjee D, Lemmer HH. Predicting the Per-formance of Bowlers in IPL: an Application of Artificial Neu-ral Network. International Journal of Performance Analysis in Sport. 2012; 12: 75–89.

[26] Hagenbuchner M, Cliff DP, Trost SG, Van Tuc N, Peoples GE. Prediction of activity type in preschool children using machine learning techniques. Journal of Science and Medicine in Sport. 2015; 18: 426–431.

[27] Akay MF, Inan C, Bradshaw DI, George JD. Support vector re-gression and multilayer feed forward neural networks for non-exercise prediction of VO. Expert Systems with Applications. 2009; 36: 10112–10119.

[28] Lee SH, Ju HS, Lee SH, Kim SW, Park HY, Kang SW, et al. Estimation of Health-Related Physical Fitness (HRPF) Levels of the General Public Using Artificial Neural Network with the National Fitness Award (NFA) Datasets. International journal of environmental research and public health. 2021; 18: 10391.

[29] Park HY, Jung H, Lee S, Kim JW, Cho HL, Nam SS. Esti-mated Artificial Neural Network Modeling of Maximal Oxygen Uptake Based on Multistage 10-m Shuttle Run Test in Healthy Adults. International Journal of Environmental Research and Public Health. 2021; 18: 8510.

[30] Ramírez-Lechuga J, Ruiz JR, Ortega FB, Benitez JM, Arauzo-Azofra A, Sanchez-Muñoz C, et al. Use of Artificial Neural Network-based Equation for estimating VO2max in adolescents. Medicine & Science in Sports & Exercise. 2008; 40: S197.

[31] Ruiz JR, Ramirez-Lechuga J, Ortega FB, Castro-Piñero J, Ben-itez JM, Arauzo-Azofra A, et al. Artificial neural network-based equation for estimating VO2max from the 20 m shuttle run test in adolescents. Artificial Intelligence in Medicine. 2008; 44: 233–245.

[32] Inoue Y, Nakao M. Prediction of maximal oxygen uptake by squat test in men and women. The Kobe Journal of Medical Sci-ences. 1996; 42: 119–129.

[33] Papini G, Bonomi AG, Stut W, Kraal JJ, Kemps HMC, Sartor F. Proof of concept of a 45-second cardiorespiratory fitness self-test for coronary artery disease patients based on accelerometry. PLoS ONE. 2017; 12: e0183740.

[34] Haramura M, Takai Y, Yoshimoto T, Yamamoto M, Kanehisa H. Cardiorespiratory and metabolic responses to body mass-based squat exercise in young men. Journal of Physiological Anthro-pology. 2017; 36: 14.

[35] Mayorga-Vega D, Aguilar-Soto P, Viciana J. Criterion-Related Validity of the 20-M Shuttle Run Test for Estimating Cardiores-piratory Fitness: A Meta-Analysis. Journal of Sports Science & Medicine. 2015; 14: 536–547.

[36] Lamoneda J, Huertas-Delgado FJ, Cadenas-Sanchez C. Feasi-bility and concurrent validity of a cardiorespiratory fitness test based on the adaptation of the original 20 m shuttle run: the 20 m shuttle run with music. Journal of Sports Sciences. 2021; 39: 57–63.

[37] Zou Z, Chen P, Yang Y, Xiao M, Wang Z. Assessment of physical fitness and its correlates in Chinese children and adolescents in Shanghai using the multistage 20‐M shuttle‐run test. American Journal of Human Biology. 2019; 31: e23148.

[38] Ekren PK. A comparison of maximal oxygen uptake obtained from different tests in chronic obstructive pulmonary disease pa-tients. Turkish Journal of Thoracic and Cardiovascular Surgery. 2014; 22: 88–94.

[39] Alves R, Lima MM, Fonseca C, Dos Reis R, Figueiredo PH, Costa H, et al. Peak oxygen uptake during the incremental shut-tle walk test in a predominantly female population with Cha-gas heart disease. European Journal of Physical & Rehabilitation Medicine. 2016; 52: 20–27.

[40] Ozalp O, Inal‐Ince D, Cakmak A, Calik‐Kutukcu E, Saglam M, Savci S, et al. High‐intensity inspiratory muscle training in bronchiectasis: a randomized controlled trial. Respirology. 2019; 24: 246–253.

[41] Barlow R, Jones B, Rogerson M, Bannister H, Stuart R, Iqbal J, et al. An Evaluation of Service Provision and Novel Strength Assessment on Patient Outcomes in a UK-Based Pulmonary Re-habilitation Setting. Journal of Chronic Obstructive Pulmonary Disease. 2020; 17: 280–288.

[42] Malek MH, Berger DE, Housh TJ, Coburn JW, Beck TW. Va-lidity of VO2max equations for aerobically trained males and females. Medicine and Science in Sports and Exercise. 2004; 36: 1427–1432.

[43] Sawyer BJ, McMahon N, Thornhill KL, Baughman BR, Ma-honey JM, Pattison KL, et al. Supra-Versus Submaximal Cy-cle Ergometer Verification of VO2max in Males and Females. Sports. 2020; 8: 163.

[44] Maldonado-Martin S, Mujika I, Padilla S. Physiological vari-ables to use in the gender comparison in highly trained runners. The Journal of Sports Medicine and Physical Fitness. 2004; 44: 8–14.