scholarly journals Development and Validation of 3 Min Incremental Step-in-Place Test for Predicting Maximal Oxygen Uptake in Home Settings: A Submaximal Exercise Study to Assess Cardiorespiratory Fitness

2021 ◽  
Vol 18 (20) ◽  
pp. 10750
Author(s):  
Fang Li ◽  
Chun-Hao Chang ◽  
Yu-Chun Chung ◽  
Huey-June Wu ◽  
Nai-Wen Kan ◽  
...  
Keyword(s):  
Oxygen Uptake ◽  
Maximal Oxygen Uptake ◽  
Prediction Models ◽  
Submaximal Exercise ◽  
Standard Errors ◽  
Post Exercise ◽  
The Third ◽  
Minute Post ◽  
Development And Validation ◽  
Incremental Step

The purpose of this research was to develop the 3 min incremental step-in-place (3MISP) test for predicting maximal oxygen uptake (V•O2max). A total of 205 adults (20–64 years) completed the 3MISP and V•O2max tests. Using age, gender, body composition (BC) including percent body fat (PBF) or body mass index (BMI), and with or without heart rate (HR) at the beginning of exercise (HR0) or difference between HR at the third minute during the exercise and the first minute post exercise (ΔHR3 − HR4) in the 3MISP test, six V•O2max prediction models were derived from multiple linear regression. Age (r = −0.239), gender (r = 0.430), BMI (r = −0.191), PBF (r = −0.706), HR0 (r = −0.516), and ΔHR3 − HR4 (r = 0.563) were significantly correlated to V•O2max. Among the six V•O2max prediction models, the PBF model∆HR3 − HR4 has the highest accuracy. The simplest models with age, gender, and PBF/BMI explained 54.5% of the V•O2max in the PBF modelBC and 39.8% of that in the BMI modelBC. The addition of HR0 and ∆HR3 − HR4 increases the variance of V•O2max explained by the PBF and BMI models∆HR3 − HR4 by 17.98% and 45.23%, respectively, while standard errors of estimate decrease by 10.73% and 15.61%. These data demonstrate that the models established using 3MISP-HR data can enhance the accuracy of V•O2max prediction.

scholarly journals The Determination of Step Frequency in 3-min Incremental Step-in-Place Tests for Predicting Maximal Oxygen Uptake from Heart Rate Response in Taiwanese Adults

2022 ◽  
Vol 19 (1) ◽  
pp. 563
Author(s):  
Fang Li ◽  
Chun-Hao Chang ◽  
Chia-An Ho ◽  
Cheng-You Wu ◽  
Hung-Chih Yeh ◽  
...  
Keyword(s):  
Heart Rate ◽  
Oxygen Uptake ◽  
Exercise Intensity ◽  
Maximal Oxygen Uptake ◽  
Prediction Models ◽  
Cardiopulmonary Exercise Testing ◽  
Standard Errors ◽  
Step Frequency ◽  
Significant Difference ◽  
Incremental Step

The maximal oxygen uptake (VO2max) prediction models established by step tests are often used for evaluating cardiorespiratory fitness (CRF). However, it is unclear which type of stepping frequency sequence is more suitable for the public to assess the CRF. Therefore, the main purpose of this study was to test the effectiveness of two 3-min incremental step-in-place (3MISP) tests (i.e., 3MISP30s and 3MISP60s) with the same total number of steps but different step-frequency sequences in predicting VO2max. In this cross-sectional study, a total of 200 healthy adults in Taiwan completed 3MISP30s and 3MISP60s tests, as well as cardiopulmonary exercise testing. The 3MISP30s and 3MISP60s models were established through multiple stepwise regression analysis by gender, age, percent body fat, and 3MISP-heart rate. The statistical analysis included Pearson’s correlations, the standard errors of estimate, the predicted residual error sum of squares, and the Bland–Altman plot to compare the measured VO2max values and those estimated. The results of the study showed that the exercise intensity of the 3MISP30s test was higher than that of the 3MISP60s test (% heart rate reserve (HRR) during 3MISP30s vs. %HRR during 3MISP60s = 81.00% vs. 76.81%, p < 0.001). Both the 3MISP30s model and the 3MISP60s model explained 64.4% of VO2max, and the standard errors of the estimates were 4.2043 and 4.2090 mL·kg−1·min−1, respectively. The cross-validation results also indicated that the measured VO2max values and those predicted by the 3MISP30s and 3MISP60s models were highly correlated (3MISP30s model: r = 0.804, 3MISP60s model: r = 0.807, both p < 0.001). There was no significant difference between the measured VO2max values and those predicted by the 3MISP30s and 3MISP60s models in the testing group (p > 0.05). The results of the study showed that when the 3MISP60s test was used, the exercise intensity was significantly reduced, but the predictive effectiveness of VO2max did not change. We concluded that the 3MISP60s test was physiologically less stressful than the 3MISP30s test, and it could be a better choice for CRF evaluation.

scholarly journals Linear and Nonlinear Prediction Models Show Comparable Precision for Maximal Mean Speed in a 4x1000 m Field Test

2017 ◽  
Vol 16 (2) ◽  
pp. 78-87
Author(s):  
J. M. Jäger ◽  
J. Kurz ◽  
H. Müller
Keyword(s):  
Oxygen Uptake ◽  
Field Test ◽  
Maximal Oxygen Uptake ◽  
Prediction Models ◽  
Mean Squared Error ◽  
Endurance Performance ◽  
Step Test ◽  
Nonlinear Prediction ◽  
Linear And Nonlinear ◽  
Mlr Model

AbstractMaximal oxygen uptake (VO2max) is one of the most distinguished parameters in endurance sports and plays an important role, for instance, in predicting endurance performance. Different models have been used to estimate VO2max or performance based on VO2max. These models can use linear or nonlinear approaches for modeling endurance performance. The aim of this study was to estimate VO2max in healthy adults based on the Queens College Step Test (QCST) as well as the Shuttle Run Test (SRT) and to use these values for linear and nonlinear models in order to predict the performance in a maximal 1000 m run (i.e. the speed in an incremental 4×1000 m Field Test (FT)). 53 female subjects participated in these three tests (QCST, SRT, FT). Maximal oxygen uptake values from QCST and SRT were used as (a) predictor variables in a multiple linear regression (MLR) model and as (b) input variables in a multilayer perceptron (MLP) after scaling in preprocessing. Model output was speed [km·h−1] in a maximal 1000 m run. Maximal oxygen uptake values estimated from QCST (40.8 ± 3.5 ml·kg−1·min−1) and SRT (46.7 ± 4.5 ml·kg−1·min−1) were significantly correlated (r = 0.38, p < 0.01) and maximal mean speed in the FT was 12.8 ± 1.6 km·h−1. Root mean squared error (RMSE) of the cross validated MLR model was 0.89 km·h−1while it was 0.95 km·h−1for MLP. Results showed that the accuracy of the applied MLP was comparable to the MLR, but did not outperform the linear approach.

scholarly journals Predictive Performance Models in Long-Distance Runners: A Narrative Review

2020 ◽  
Vol 17 (21) ◽  
pp. 8289
Author(s):  
José Alvero-Cruz ◽  
Elvis Carnero ◽  
Manuel García ◽  
Fernando Alacid ◽  
Lorena Correas-Gómez ◽  
...  
Keyword(s):  
Oxygen Uptake ◽  
Maximal Oxygen Uptake ◽  
Prediction Models ◽  
Exercise Physiology ◽  
Field Tests ◽  
Training Load ◽  
Running Economy ◽  
Anthropometric Parameters ◽  
Long Distance ◽  
Physiological Variables

Physiological variables such as maximal oxygen uptake (VO2max), velocity at maximal oxygen uptake (vVO2max), running economy (RE) and changes in lactate levels are considered the main factors determining performance in long-distance races. The aim of this review was to present the mathematical models available in the literature to estimate performance in the 5000 m, 10,000 m, half-marathon and marathon events. Eighty-eight articles were identified, selections were made based on the inclusion criteria and the full text of the articles were obtained. The articles were reviewed and categorized according to demographic, anthropometric, exercise physiology and field test variables were also included by athletic specialty. A total of 58 studies were included, from 1983 to the present, distributed in the following categories: 12 in the 5000 m, 13 in the 10,000 m, 12 in the half-marathon and 21 in the marathon. A total of 136 independent variables associated with performance in long-distance races were considered, 43.4% of which pertained to variables derived from the evaluation of aerobic metabolism, 26.5% to variables associated with training load and 20.6% to anthropometric variables, body composition and somatotype components. The most closely associated variables in the prediction models for the half and full marathon specialties were the variables obtained from the laboratory tests (VO2max, vVO2max), training variables (training pace, training load) and anthropometric variables (fat mass, skinfolds). A large gap exists in predicting time in long-distance races, based on field tests. Physiological effort assessments are almost exclusive to shorter specialties (5000 m and 10,000 m). The predictor variables of the half-marathon are mainly anthropometric, but with moderate coefficients of determination. The variables of note in the marathon category are fundamentally those associated with training and those derived from physiological evaluation and anthropometric parameters.

scholarly journals A Systematic Review and Meta-Analysis of Submaximal Exercise-Based Equations to Predict Maximal Oxygen Uptake in Young People

2014 ◽  
Vol 26 (3) ◽  
pp. 342-357 ◽  
Author(s):  
Katia Ferrar ◽  
Harrison Evans ◽  
Ashleigh Smith ◽  
Gaynor Parfitt ◽  
Roger Eston
Keyword(s):  
Systematic Review ◽  
Young People ◽  
Oxygen Uptake ◽  
Maximal Oxygen Uptake ◽  
Meta Analysis ◽  
Submaximal Exercise ◽  
Gas Analysis ◽  
Exercise Tests ◽  
Exercise Mode ◽  
Selection Of

Many equations to predict maximal oxygen uptake (V̇O2max) from submaximal exercise tests have been proposed for young people, but the composition and accuracy of these equations vary greatly. The purpose of this systematic review was to analyze all submaximal exercise-based equations to predict V̇O2max measured via direct gas analysis for use with young people. Five databases were systematically searched in February 2013. Studies were included if they used a submaximal, exercise-based method to predict V̇O2max; the actual V̇O2max was gas analyzed; participants were younger than 18 years; and equations included at least one submaximal exercise-based variable. A meta-analysis and narrative synthesis were conducted. Sixteen studies were included. The mean equation validity statistic was strong, r = .786 (95% CI 0.747–0.819). Subgroup meta-analysis suggests exercise mode may contribute to the overall model, with running- and walking-based predictive equations reporting the highest mean r values (running r = .880; walking r = .821) and cycling the weakest (r = .743). Selection of the most appropriate equation should be guided by factors such as purpose, logistic limitations, appropriateness of the validation sample, the level of study bias, and the degree of accuracy. Suggestions regarding the most accurate equation for each exercise mode are provided.

Submaximal Exercise–Based Equations to Predict Maximal Oxygen Uptake in Older Adults: A Systematic Review

2016 ◽  
Vol 97 (6) ◽  
pp. 1003-1012 ◽  
Author(s):  
Ashleigh E. Smith ◽  
Harrison Evans ◽  
Gaynor Parfitt ◽  
Roger Eston ◽  
Katia Ferrar
Keyword(s):  
Systematic Review ◽  
Older Adults ◽  
Oxygen Uptake ◽  
Maximal Oxygen Uptake ◽  
Submaximal Exercise

REPEATED MEASUREMENTS OF AEROBIC CAPACITY DURING A WEEK OF INTENSIVE TRAINING AT A YOUTHS' TRACK CAMP

1967 ◽  
Vol 45 (5) ◽  
pp. 805-811 ◽  
Author(s):  
Gordon R. Cumming ◽  
A. Goodwin ◽  
G. Baggley ◽  
Jack Antel
Keyword(s):  
Oxygen Uptake ◽  
Pulse Rate ◽  
Aerobic Capacity ◽  
Physical Training ◽  
Maximal Oxygen Uptake ◽  
Constant Load ◽  
Submaximal Exercise ◽  
Repeated Measurements ◽  
Intensive Training ◽  
Run Up

The maximal oxygen uptake of six boys and six girls, 18 to 16 years of age, showed no change with twice daily measurements over a 6-day period at a track camp where intensive physical training was carried out. Over the 6 days, submaximal pulse rate declined 6 beats/min for a constant load, and maximal pulse rate declined 7 beats/min. Boys and girls 13 to 16 years of age may run up to 45 miles daily without producing measurable declines in maximal oxygen uptake. Submaximal exercise pulse rates were higher in the evening compared with the morning. There was a tendency for submaximal exercise pulse rates to decline during training before any increase in aerobic capacity occurred. A prediction of aerobic capacity from submaximal tests based on pulse rate did not give a true indication of changes in aerobic capacity.

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