Prediction of VO2 peak using OMNI Ratings of Perceived Exertion from a submaximal cycle exercise test. Academic Article uri icon

start page

  • 863

end page

  • 881

abstract

  • The primary aim of this study was to develop statistical models to predict peak oxygen consumption (VO2 peak) using OMNI Ratings of Perceived Exertion measured during submaximal cycle ergometry. Male (M = 20.9 yr., SE = 0.4) and female (M = 21.6 yr., SE = 0.5) participants (N = 81) completed a load-incremented maximal cycle ergometer exercise test. Simultaneous multiple linear regression was used to develop separate VO2 peak statistical models using submaximal ratings of perceived exertion for the overall body, legs, and chest/breathing as predictor variables. VO2 peak (L·min(-1)) predicted for men and women from ratings of perceived exertion for the overall body (3.02 ± 0.06; 2.03 ± 0.04), legs (3.02 ± 0.06; 2.04 ± 0.04), and chest/breathing (3.02 ± 0.05; 2.03 ± 0.03) were similar to measured VO2 peak (3.02 ± 0.10; 2.03 ± 0.06, ps > .05). Statistical models based on submaximal OMNI Ratings of Perceived Exertion provide an easily administered and accurate method to predict VO2 peak.

date/time value

  • June 2014

Digital Object Identifier (DOI)

  • 10.2466/27.29.PMS.118k28w7

PubMed Identifier

  • 25068750

volume

  • 118

number

  • 3

keywords

  • Adult
  • Bicycling
  • Ergometry
  • Female
  • Heart Rate
  • Humans
  • Male
  • Models, Statistical
  • Oxygen Consumption
  • Physical Exertion
  • Predictive Value of Tests
  • Self Concept
  • Young Adult