A 45-Second Self-Test for Cardiorespiratory Fitness: Heart Rate-Based Estimation in Healthy Individuals

Cardio-respiratory fitness (CRF) is a widespread essential indicator in Sports Science as well as in Sports Medicine. This study aimed to develop and validate a prediction model for CRF based on a 45 second self-test, which can be conducted anywhere. Criterion validity, test re-test study was set up...

Full description

Saved in:
Bibliographic Details
Published inPloS one Vol. 11; no. 12; p. e0168154
Main Authors Sartor, Francesco, Bonato, Matteo, Papini, Gabriele, Bosio, Andrea, Mohammed, Rahil A, Bonomi, Alberto G, Moore, Jonathan P, Merati, Giampiero, La Torre, Antonio, Kubis, Hans-Peter
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 13.12.2016
Public Library of Science (PLoS)
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Cardio-respiratory fitness (CRF) is a widespread essential indicator in Sports Science as well as in Sports Medicine. This study aimed to develop and validate a prediction model for CRF based on a 45 second self-test, which can be conducted anywhere. Criterion validity, test re-test study was set up to accomplish our objectives. Data from 81 healthy volunteers (age: 29 ± 8 years, BMI: 24.0 ± 2.9), 18 of whom females, were used to validate this test against gold standard. Nineteen volunteers repeated this test twice in order to evaluate its repeatability. CRF estimation models were developed using heart rate (HR) features extracted from the resting, exercise, and the recovery phase. The most predictive HR feature was the intercept of the linear equation fitting the HR values during the recovery phase normalized for the height2 (r2 = 0.30). The Ruffier-Dickson Index (RDI), which was originally developed for this squat test, showed a negative significant correlation with CRF (r = -0.40), but explained only 15% of the variability in CRF. A multivariate model based on RDI and sex, age and height increased the explained variability up to 53% with a cross validation (CV) error of 0.532 L ∙ min-1 and substantial repeatability (ICC = 0.91). The best predictive multivariate model made use of the linear intercept of HR at the beginning of the recovery normalized for height2 and age2; this had an adjusted r2 = 0. 59, a CV error of 0.495 L·min-1 and substantial repeatability (ICC = 0.93). It also had a higher agreement in classifying CRF levels (κ = 0.42) than RDI-based model (κ = 0.29). In conclusion, this simple 45 s self-test can be used to estimate and classify CRF in healthy individuals with moderate accuracy and large repeatability when HR recovery features are included.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ObjectType-Undefined-3
Conceptualization: FS HPK.Data curation: FS.Formal analysis: FS MB GP AGB.Investigation: MB RAM AB FS JPM GM ALT.Methodology: FS HPK.Project administration: FS HPK ALT.Resources: HPK JPM ALT AB FS.Software: FS GP AGB.Supervision: FS HPK JPM GM ALT.Validation: FS.Visualization: FS GP.Writing – original draft: FS.Writing – review & editing: FS HPK JPM MB AB AGB.
Competing Interests: The authors have read the journal's policy and the authors of this manuscript have the following competing interests: F.S. and A.G.B. work for Philips Research; G.P. was doing an internship at Philips Research during his contribution in this work. A.B. works for Mapei Sport. All other authors have no conflict of interest. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0168154