Prediction Of Maximal Oxygen Uptake Research Articles

Confirmatory Study on Prediction of Maximal Oxygen Uptake by Ensemble Learning Algorithm

Objective: The prediction model of maximal oxygen uptake (VO2max) was established by different ensemble learning methods. Compared with multiple linear regression, a common prediction method of VO2max, the effectiveness of the ensemble learning model is verified, and screen out the optimal VO2max prediction model. Methods: A total of 84 male college students, were recruited, informed of the purpose and procedure of the experiment, and passed the PAR-Q questionnaire screening. Cardiopulmonary Exercise Test (CPET), lung function, body composition test, VO2max, minute ventilation volume (VE), tidal volume (Vt), weight, and other related indicators. After the correlation analysis of the experimental results, a VO2max multiple linear regression model and an ensemble learning prediction model are computed. Results: The indicators that finally enter the multiple linear regression equation include: weight, Vt, VE. The regression equation is: VO2max (ml/kg/min) = 52.455+0.005×VT (ml/min) + 0.111×VE (L/min)-0.441×weight (kg), and the regression coefficient test results is extremely significant (P<0.01). The VO2max prediction model is computed by using the ensemble learning algorithm and among the five prediction models, it is found that Weighted average (R^2=0.7715) has the best effect, and higher than multiple regression model, there is no significant difference between the actual value and the predicted value VO2max (P>0.05). Conclusion: In the case of a small sample size, the weighted average model predicts VO2max the most accurately, compared with multiple regression models, the ensemble learning model can include more basic indicators, the evaluation of VO2max in the body is more comprehensive, and the prediction results are more accurate.

Prediction of maximal oxygen uptake based on anthropometric indices in Iranian male adults.

Assessment of maximal oxygen consumption is important in both general community and occupational settings. Validity and reliability tests are needed to indicate the functionality of the cardiopulmonary system. This study aimed to establish a maximal oxygen consumption (VO2max) prediction model using anthropometric and demographic variables for young adults in Iran. This cross-sectional study was conducted on 64 healthy young men aged 19-29 years. Oxygen consumption was measured directly and the prediction models to estimate VO2max were determined by multiple linear regression. The accuracy of the prediction models was considered using regression coefficient (R), coefficient of determination (R2), and standard error of estimate (SEE). The average VO2max was 44.02±4.31 ml/kg/min. Significant correlations were found between the measured VO2max and the anthropometric and demographic variables (r = 0.16-0.86, P < 0.05). Three significant regression models with acceptable accuracy were developed (R2 = 0.67-0.71, SEE = 3.19-3.21). The predictive models consisted of 3-5 variables as significant predictors of VO2max and had acceptable accuracy for Iranian young adults. The proposed models are a simple and valid tool that can be used to estimate the VO2max in the field and in laboratory settings.

Maximal oxygen uptake prediction from submaximal bicycle ergometry using a differential model

The maximal oxygen uptake (VO2max) estimation has been a subject of research for many years. Cardiorespiratory measurements during incremental tests until exhaustion are considered the golden yard stick to assess VO2max. However, precise VO2max determination based on submaximal tests is attractive for athlete as well for clinical populations. Here, we propose and verify such a method based on experimental data. Using a recently developed model of heart rate (HR) and VO2 kinetics in graded exercise tests, we applied a protocol, which is terminated at 80% of the estimated maximal HR during ergometer cycling. In our approach, initially, formula for maximal HR is selected by retrospective study of a reference population (17 males, 23.5 ± 2.0 years, BMI: 23.9 ± 3.2 kg/m2). Next, the subjects for experimental group were invited (nine subjects of both sexes: 25.1 ± 2.1 years, BMI 23.2 ± 2.2 kg/m2). After calculation of maximal HR using cardiorespiratory recordings from the submaximal test, VO2max is predicted. Finally, we compared the prediction with the values from the maximal exercise test. The differences were quantified by relative errors, which vary from 1.2% up to 13.4%. Some future improvements for the procedure of VO2max prediction are discussed. The experimental protocol may be useful for application in rehabilitation assessment and in certain training monitoring settings, since physical exertion is not a prerequisite and the approach provides an acceptable VO2max estimation accuracy.

Validity and Reliability of New Equations for the Prediction of Maximal Oxygen Uptake in Male and Female Elite Adolescent Rowers.

The aim of this study was to develop accurate, reliable, and reproductive equations for the prediction of maximum oxygen uptake (O2max) in male and female high-level adolescent rowers. This study included two parts. In the first part, V̇O2max was evaluated in 106 male and 83 female high-level adolescent rowers during an incremental step test (IRT) on a rowing ergometer, and stepwise multiple regression analyses were used for the development of new equations. In the second part, these equations were tested in 26 new high-level adolescent rowers of the same age and anthropometrical characteristics (boys: 15.27 ± 2.70 yrs and 15.34 ± 2.80 yrs; 72.37 ± 10.96 kg and 70.96 ± 10.65 kg; girls: 15.00 ± 2.11 yrs and 15.94 ± 2.71 yrs; 62.50 ± 7.14 kg and 63.41 ± 6.72 kg for parts 1 and 2, respectively; p > 0.05). V̇O2max was predicted from the combination of lean body mass (LBM) and the distance covered during the last 4 min stage of the IRT (boys: r2 = 0.715, F = 68.74, p = 0.001; girls: r2 = 0.769, F = 57.81, p = 0.001). In the second part, no significant differences were identified when the new equations were tested against measured V̇O2max (boys: 3971.15 ± 713.38 mL·min−1 vs. 3915.83 ± 704.43 mL·min−1; girls: 3272.75 ± 551.46 mL·min−1 vs. 3308.94 ± 557.59 mL·min−1 for measured and predicted values, respectively; p > 0.05). In conclusion, V̇O2max of high-level adolescent rowers can be predicted with high accuracy, reliability, and repeatability using simple and easily evaluated anthropometric and performance variables.

Prediction of maximal oxygen uptake from 6-min walk test in pulmonary hypertension.

Maximal oxygen uptake (V′O2max), assessed by cardiopulmonary exercise testing (CPET), is an important parameter for risk assessment in patients with pulmonary hypertension (PH). However, CPET may not be available for all PH patients. Thus, we aimed to test previously published predictive models of V′O2max from the 6-min walk distance (6MWD) for their accuracy and to create a new model.We tested four models (two by Ross et al. (2010), one by Miyamoto et al. (2000) and one by Zapico et al. (2019)). To derive a new model, data were split into a training and testing dataset (70:30) and step-wise linear regression was performed. To compare the different models, the standard error of the estimate (SEE) was calculated and the models graphically compared by Bland–Altman plots. Sensitivity and specificity for correct prediction into low-risk classification (V′O2max >15 mL/min/kg) was calculated for all models.A total of 276 observations were included in the analysis (194/82 training/testing dataset); 6MWD and V′O2max were significantly correlated (r=0.65, p<0.001). Linear regression showed significant correlation of 6MWD, weight and heart rate response (HRR) with V′O2max and the best fitting prediction equation was: V′O2max = 1.83 + 0.031 × 6MWD (m) – 0.023 × weight (kg) – 0.015 × HRR (bpm). SEEs for the different models were 3.03, 3.22, 4.36 and 3.08 mL/min/kg for the Ross et al., Miyamoto et al., Zapico et al. models and the new model, respectively. Predicted mean V′O2max was 16.5 mL/min/kg (versus observed 16.1 mL/min/kg).6MWD and V′O2max reveal good correlation in all models. However, the accuracy of all models is inadequate for clinical use. Thus, CPET and 6MWD both remain valuable risk assessment tools in the management of PH.

Contribution of Body Mass Index Stratification for the Prediction of Maximal Oxygen Uptake.

The purpose of this study was to investigate whether modeling within separate body mass index (BMI) stratifications improves the accuracy of maximal oxygen uptake (VO2max) prediction compared to a model developed regardless of adults' BMIs. A total of 250 Taiwanese adults (total group, TOG) aged 22-64 years participated in this study, and were stratified into a normal group (NOG: 135), an overweight group (OVG: 69), and an obesity group (OBG: 46), according to the BMI classification recommended by the Taiwan Ministry of Health and Welfare. VO2max was directly measured on an electromagnetic bicycle ergometer. Using the participant's heart rate in the 3-min incremental step-in-place test and demographic parameters, VO2max prediction models established for four groups were TOG model, NOG model, OVG model, and OBG model, respectively. Compared with the TOG model, the OVG and OBG models had higher coefficients of determination and lower standard error of estimates (SEEs), or %SEEs. The validities of the NOG (r = 0.780), OVG (r = 0.776), and OBG (r = 0.791) models for BMI subgroups increased by 1.79%, 4.64%, and 8.22% respectively, and the reliabilities (NOG model: ICC = 0.755; OVG model: ICC = 0.765; OBG model: ICC = 0.779) increased by 3.18%, 3.27%, and 9.63%, respectively. These results suggested using separate models established in BMI stratifications can effectively improve the prediction of VO2max.

Prediction of Maximal Oxygen Uptake From Submaximal Exercise Testing in Chronic Respiratory Patients. New Perspectives

Prediction of Maximal Oxygen Uptake From Submaximal Exercise Testing in Chronic Respiratory Patients. New Perspectives

Prediction of Maximal Oxygen Uptake by Six-Minute Walk Test and Body Mass Index in Healthy Boys

To develop an equation to predict maximal oxygen uptake (VO2max) based on the 6-minute walk test (6MWT) and body composition in healthy boys. Direct VO2max, 6-minute walk distance, and anthropometric characteristics were measured in 349 healthy boys (12.49 ± 2.72 years). Multiple regression analysis was used to generate VO2max prediction equations. Cross-validation of the VO2max prediction equations was assessed with predicted residual sum of squares statistics. Pearson correlation was used to assess the correlation between measured and predicted VO2max. Objectively measured VO2max had a significant correlation with demographic and 6MWT characteristics (R = 0.11-0.723, P < .01). Multiple regression analysis revealed the following VO2max prediction equation: VO2max (mL/kg/min) = 12.701 + (0.06 × 6-minute walk distance m) - (0.732 × body mass indexkg/m2) (R2 = 0.79, standard error of the estimate [SEE] = 2.91 mL/kg/min, %SEE = 6.9%). There was strong correlation between measured and predicted VO2max (r = 0.875, P < .001). Cross-validation revealed minimal shrinkage (R2p = 0.78 and predicted residual sum of squares SEE = 2.99 mL/kg/min). This study provides a relatively accurate and convenient VO2max prediction equation based on the 6MWT and body mass index in healthy boys. This model can be used for evaluation of cardiorespiratory fitness of boys in different settings.

How Accurate Is the Prediction of Maximal Oxygen Uptake with Treadmill Testing?

BackgroundCardiorespiratory fitness measured by treadmill testing has prognostic significance in determining mortality with cardiovascular and other chronic disease states. The accuracy of a recently developed method for estimating maximal oxygen uptake (VO2peak), the heart rate index (HRI), is dependent only on heart rate (HR) and was tested against oxygen uptake (VO2), either measured or predicted from conventional treadmill parameters (speed, incline, protocol time).MethodsThe HRI equation, METs = 6 x HRI– 5, where HRI = maximal HR/resting HR, provides a surrogate measure of VO2peak. Forty large scale treadmill studies were identified through a systematic search using MEDLINE, Google Scholar and Web of Science in which VO2peak was either measured (TM-VO2meas; n = 20) or predicted (TM-VO2pred; n = 20) based on treadmill parameters. All studies were required to have reported group mean data of both resting and maximal HRs for determination of HR index-derived oxygen uptake (HRI-VO2).ResultsThe 20 studies with measured VO2 (TM-VO2meas), involved 11,477 participants (median 337) with a total of 105,044 participants (median 3,736) in the 20 studies with predicted VO2 (TM-VO2pred). A difference of only 0.4% was seen between mean (±SD) VO2peak for TM- VO2meas and HRI-VO2 (6.51±2.25 METs and 6.54±2.28, respectively; p = 0.84). In contrast, there was a highly significant 21.1% difference between mean (±SD) TM-VO2pred and HRI-VO2 (8.12±1.85 METs and 6.71±1.92, respectively; p<0.001).ConclusionAlthough mean TM-VO2meas and HRI-VO2 were almost identical, mean TM-VO2pred was more than 20% greater than mean HRI-VO2.

Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances.

Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance.

Validation of a single-stage fixed-rate step test for the prediction of maximal oxygen uptake in healthy adults.

Healthcare professionals with limited access to ergospirometry remain in need of valid and simple submaximal exercise tests to predict maximal oxygen uptake (VO2max ). Despite previous validation studies concerning fixed-rate step tests, accurate equations for the estimation of VO2max remain to be formulated from a large sample of healthy adults between age 18-75years (n>100). The aim of this study was to develop a valid equation to estimate VO2max from a fixed-rate step test in a larger sample of healthy adults. A maximal ergospirometry test, with assessment of cardiopulmonary parameters and VO2max , and a 5-min fixed-rate single-stage step test were executed in 112 healthy adults (age 18-75years). During the step test and subsequent recovery, heart rate was monitored continuously. By linear regression analysis, an equation to predict VO2max from the step test was formulated. This equation was assessed for level of agreement by displaying Bland-Altman plots and calculation of intraclass correlations with measured VO2max . Validity further was assessed by employing a Jackknife procedure. The linear regression analysis generated the following equation to predict VO2max (lmin(-1) ) from the step test: 0·054(BMI)+0·612(gender)+3·359(body height in m)+0·019(fitness index)-0·012(HRmax)-0·011(age)-3·475. This equation explained 78% of the variance in measured VO2max (F=66·15, P<0·001). The level of agreement and intraclass correlation was high (ICC=0·94, P<0·001) between measured and predicted VO2max . From this study, a valid fixed-rate single-stage step test equation has been developed to estimate VO2max in healthy adults. This tool could be employed by healthcare professionals with limited access to ergospirometry.

The Use of an Indoor Rowing Ergometer Test for the Prediction of Maximal Oxygen Uptake

The Use of an Indoor Rowing Ergometer Test for the Prediction of Maximal Oxygen Uptake based version of the multi stage fitness test.Methods: Forty one participants (25 men, 16 women; mean ± SD; age 21 ± 5.3 years, height 175.4 ± 8.1cm, body mass 71.4 ± 12.6 kg) completed in a counter-balanced design: a treadmill running maximal oxygen uptake test (Treadmill - VO2max), a 2,000 m timed row and an incremental rowing maximal oxygen uptake test (IRT - VO2max) where stroke rate was increased by one stroke each minute. A student’s paired sample t-test was used to determine differences in maximal oxygen uptake (VO2max) and heart rate (HRmax) and a Pearson correlation coefficient to measure the relationships between VO2 during tests. Results: VO2max values were significantly higher in treadmill - VO2max (44.7 ± 6.5 ml•kg-1•min-1) than IRT - VO2max (42.2 ± 7.3 ml•kg-1•min-1; P<0.05). Maximum heart rate was significantly higher during the treadmill - VO2max (192 ± 10 beats.min-1) compared to the IRT - VO2max (184.3 ± 10.6 beats.min-1; P<0.05). A significant correlation was observed between treadmill - VO2max and the IRT - VO2max for VO2 (r=0.67). Gender specific linear regression equations were created to predict VO2max on the IRT from submaximal data (Males: Predicted VO2max (ml•kg-1•min-1)=2.30 (x) + 20.8, SEE=4.5; Females Predicted VO2max (ml•kg-1•min-1)=1.93(x) + 19.4, SEE=3.7). Conclusion: This new stroke rate based IRT provides a continuous test to exhaustion with minimal equipment which is suitable for the regular gym user to monitor their cardiorespiratory fitness.

Prediction of Maximal Oxygen Uptake From a 3-Minute Walk Based on Gender, Age, and Body Composition

The purpose was to develop new maximal oxygen uptake (VO2max) prediction models using a perceptually regulated 3-minute walk test. VO2max was measured with a maximal incremental cycle test in 283 Japanese adults. A 3-minute walk test was conducted at a self-regulated intensity corresponding to ratings of perceived exertion (RPE) 13. A 3-minute walk distance (3MWD) was significantly related to VO2max (r = .60, P < .001). Three prediction models were developed by multiple regression to estimate VO2max using data on gender, age, 3MWD, and either BMI [BMI model, multiple correlation coefficients (R) = .78, standard error of estimate (SEE) = 5.26 ml·kg-1·min-1], waist circumference (WC model, R = .80, SEE = 5.04 ml·kg-1·min-1), or body fat percentage (%Fat model, R = .84, SEE = 4.57 ml·kg-1·min-1), suggesting that the %Fat model is the best model [VO2max = 37.501 + 0.463 × Gender (0 = women, 1 = men) - 0.195 × Age - 0.589 × %Fat + 0.053 × 3MWD]. Cross-validation by using the predicted residual sum of squares (PRESS) procedures demonstrated a high level of cross-validity of all prediction models. The new VO2max prediction models are reasonably applicable to estimating VO2max in Japanese adults and represent a quick, low-risk, and convenient means for estimating VO2max in the field.

Prediction of maximal oxygen uptake from submaximal and maximal exercise on a ski ergometer

Prediction of maximal oxygen uptake from submaximal and maximal exercise on a ski ergometer

RETRACTED ARTICLE: Prediction of maximal oxygen uptake from ratings of perceived exertion and heart rate during running: the effect of age

RETRACTED ARTICLE: Prediction of maximal oxygen uptake from ratings of perceived exertion and heart rate during running: the effect of age

Non-exercise Prediction Of Maximal Oxygen Uptake With The Objectively Measured Physical Activity In Japanese Men

Non-exercise Prediction Of Maximal Oxygen Uptake With The Objectively Measured Physical Activity In Japanese Men

The Accuracy of Non-Exercise Maximal Oxygen Uptake Prediction Equations for Cross Country Athletes

The Accuracy of Non-Exercise Maximal Oxygen Uptake Prediction Equations for Cross Country Athletes

Prediction of maximal oxygen uptake from submaximal ratings of perceived exertion and heart rate during a continuous exercise test: the efficacy of RPE 13

This study assessed the utility of a single, continuous exercise protocol in facilitating accurate estimates of maximal oxygen uptake V(O)(2max) from submaximal heart rate (HR) and the ratings of perceived exertion (RPE) in healthy, low-fit women, during cycle ergometry. Eleven women estimated their RPE during a continuous test (1 W 4 s(-1)) to volitional exhaustion (measured V(O)(2max)). Individual gaseous exchange thresholds (GETs) were determined retrospectively. The RPE and HR values prior to and including an RPE 13 and GET were extrapolated against corresponding oxygen uptake to a theoretical maximal RPE (20) and peak RPE (19), and age-predicted HRmax, respectively, to predict V(O)(2max)). There were no significant differences (P > 0.05) between measured (30.9 +/- 6.5 ml kg(-1) min(-1)) and predicted V(O)(2max) from all six methods. Limits of agreement were narrowest and intraclass correlations were highest for predictions of V(O)(2max) from an RPE 13 to peak RPE (19). Prediction of V(O)(2max) from a regression equation using submaximal HR and work rate at an RPE 13 was also not significantly different to actual V(O)(2max) (R( 2 ) = 0.78, SEE = 3.42 ml kg(-1) min(-1), P > 0.05). Accurate predictions of V(O)(2max) may be obtained from a single, continuous, estimation exercise test to a moderate intensity (RPE 13) in low-fit women, particularly when extrapolated to peak terminal RPE (RPE(19)). The RPE is a valuable tool that can be easily employed as an adjunct to HR, and provides supplementary clinical information that is superior to using HR alone.

The prediction of maximal oxygen uptake from submaximal ratings of perceived exertion elicited during the multistage fitness test

The purpose of this study was to assess whether maximal oxygen uptake (V.O2max) could be predicted from submaximal ratings of perceived exertion (RPE) elicited during the multistage fitness test (MFT)....

Prediction of maximal oxygen uptake in sedentary males from a perceptually regulated, sub-maximal graded exercise test

The purpose of this study was to assess the validity of predicting the maximal oxygen uptake ([Vdot]O2max) of sedentary men from sub-maximal [Vdot]O2 values obtained during a perceptually regulated exercise test. Thirteen healthy, sedentary males aged 29 – 52 years completed five graded exercise tests on a cycle ergometer. The first and fifth test involved a graded exercise test to determine [Vdot]O2max. The two maximal graded exercise tests were separated by three sub-maximal graded exercise tests, perceptually regulated at 3-min RPE intensities of 9, 11, 13, 15, and 17 on the Borg ratings of perceived exertion (RPE) scale, in that order. After confirmation that individual linear regression models provided the most appropriate fit to the data, the regression lines for the perceptual ranges 9 – 17, 9 – 15, and 11 – 17 were extrapolated to RPE 20 to predict [Vdot]O2max. There were no significant differences between [Vdot]O2max values from the graded exercise tests (mean 43.9 ml · kg−1 · min−1, s = 6.3) and predicted [Vdot]O2max values for the perceptual ranges 9 – 17 (40.7 ml · kg−1 · min−1, s = 2.2) and RPE 11 – 17 (42.5 ml · kg−1 · min−1, s = 2.3) across the three trials. The predicted [Vdot]O2max from the perceptual range 9 – 15 was significantly lower (P < 0.05) (37.7 ml · kg−1 · min−1, s = 2.3). The intra-class correlation coefficients between actual and predicted [Vdot]O2max for RPE 9 – 17 and RPE 11 – 17 across trials ranged from 0.80 to 0.87. Limits of agreement analysis on actual and predicted [Vdot]O2 values (bias ± 1.96 × s diff) were 3.4 ml · kg−1 · min−1 (±10.7), 2.4 ml · kg−1 · min−1 (±9.9), and 3.7 ml · kg−1 · min−1 (±12.8) (trials 1, 2, and 3, respectively) of RPE range 9 – 17. Results suggest that a sub-maximal, perceptually guided graded exercise test provides acceptable estimates of [Vdot]O2max in young to middle-aged sedentary males.