Artificial neural network-based equation for estimating VO2max from the 20m shuttle run test in adolescents

  • Authors:

  • Jonatan R. Ruiz;Jorge Ramirez-Lechuga;Francisco B. Ortega;José Castro-Piñero;Jose M. Benitez;Antonio Arauzo-Azofra;Cristobal Sanchez;Michael Sjöström;Manuel J. Castillo;Angel Gutierrez;Mikel Zabala

  • Affiliations:

  • Department of Physiology, School of Medicine, University of Granada, Granada 18012, Spain and Unit for Preventive Nutrition, Department of Biosciences and Nutrition at NOVUM, Karolinska Institutet ...;Department of Physical Education, School of Sport Sciences, University of Granada, Granada 18015, Spain;Department of Physiology, School of Medicine, University of Granada, Granada 18012, Spain and Unit for Preventive Nutrition, Department of Biosciences and Nutrition at NOVUM, Karolinska Institutet ...;Department of Physical Education, School of Education, University of Cadiz, Puerto Real 11519, Spain;Department of Computer Science and Artificial Intelligence, Escuela Técnica Superior de Ingenierías de Informática y Telecomunicación, University of Granada, Granada 18071, Spa ...;Department of Computer Science and Artificial Intelligence, Escuela Técnica Superior de Ingenierías de Informática y Telecomunicación, University of Granada, Granada 18071, Spa ...;Department of Physical Education, School of Sport Sciences, University of Granada, Granada 18015, Spain;Unit for Preventive Nutrition, Department of Biosciences and Nutrition at NOVUM, Karolinska Institutet, Huddinge SE-14157, Sweden;Department of Physiology, School of Medicine, University of Granada, Granada 18012, Spain;Department of Physiology, School of Medicine, University of Granada, Granada 18012, Spain;Department of Physical Education, School of Sport Sciences, University of Granada, Granada 18015, Spain

  • Venue:
  • Artificial Intelligence in Medicine
  • Year:
  • 2008

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Abstract

Objective: To develop an artificial neural network (ANN)-equation to estimate maximal oxygen uptake (VO"2"m"a"x) from 20m shuttle run test (20mSRT) performance (stage), sex, age, weight, and height in young persons. Methods: The 20mSRT was performed by 193 (122 boys and 71 girls) adolescents aged 13-19 years. All the adolescents wore a portable gas analyzer to measure VO"2 and heart rate during the test. The equation was developed and cross-validated following the ANN mathematical model. The neural net performance was assessed through several error measures. Agreement between the measured VO"2"m"a"x and estimated VO"2"m"a"x from Leger's and ANN equations were analysed following the Bland and Altman method. Results: The percentage error was 17.13 and 7.38 for Leger and ANN-equation (P