Cross-validation of Peak Oxygen Consumption Prediction Models from OMNI Perceived Exertion

R. J. Mays, F. L. Goss, E. F. Nagle, M. Gallagher, L. Haile, M. A. Schafer, K. H. Kim, R. J. Robertson

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This study cross-validated statistical models for prediction of peak oxygen consumption using ratings of perceived exertion from the Adult OMNI Cycle Scale of Perceived Exertion. 74 participants (men: n=36; women: n=38) completed a graded cycle exercise test. Ratings of perceived exertion for the overall body, legs, and chest/breathing were recorded each test stage and entered into previously developed 3-stage peak oxygen consumption prediction models. There were no significant differences (p>0.05) between measured and predicted peak oxygen consumption from ratings of perceived exertion for the overall body, legs, and chest/breathing within men (mean±standard deviation: 3.16±0.52 vs. 2.92±0.33 vs. 2.90±0.29 vs. 2.90±0.26 L·min-1) and women (2.17±0.29 vs. 2.02±0.22 vs. 2.03±0.19 vs. 2.01±0.19 L·min-1) participants. Previously developed statistical models for prediction of peak oxygen consumption based on subpeak OMNI ratings of perceived exertion responses were similar to measured peak oxygen consumption in a separate group of participants. These findings provide practical implications for the use of the original statistical models in standard health-fitness settings.

Original languageEnglish (US)
Pages (from-to)831-837
Number of pages7
JournalInternational Journal of Sports Medicine
Volume37
Issue number10
DOIs
StatePublished - Sep 1 2016

Bibliographical note

Funding Information:
The current study was supported by a University of Pittsburgh School of Education Research grant. Dr. Mays is principal investigator of two National Institutes of Health grants funded by the National Heart, Lung, and Blood Institute (K01HL115534) and the Mountain West Clinical Translational Research - Infrastructure Network National Institute of General Medical Sciences (under the parent award 1U54GM104944). Dr. Mays also receives funding from Providence Medical Group for the conduct of quality improvement projects. Neither of these grants or consultant work are related to the current study.

Publisher Copyright:
© Georg Thieme Verlag KG Stuttgart. New York.

Keywords

  • cycle ergometry
  • exercise testing
  • prediction equations
  • undifferentiated and differentiated RPE

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