10.5061/DRYAD.VH610
Sartor, Francesco
Bonato, Matteo
University of Milan
Papini, Gabriele
University of Pisa
Eindhoven University of Technology
Bosio, Andrea
Mohammed, Rahil A.
Bangor University
Bonomi, Alberto G.
Moore, Jonathan P.
Bangor University
Merati, Giampiero
University of Milan
La Torre, Antonio
University of Milan
Kubis, Hans-Peter
Bangor University
Data from: A 45-second self-test for cardiorespiratory fitness: heart
rate-based estimation in healthy individuals
Dryad
dataset
2017
cardiorespiratory fintess
squat-test
2017-11-17T00:00:00Z
2017-11-17T00:00:00Z
en
https://doi.org/10.1371/journal.pone.0168154
36853 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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.
Sartor_F_RD_Data_2016
Netherlands
Italy
United Kingdom