Abstract:Aerobic endurance describes the ability of the body's cardio-respiratory system to perform physical activity for an extended period of time and resist fatigue. Standard tests to determine aerobic endurance involves measuring the maximum volume of oxygen (VO 2 max) an athlete uses up while exercising at maximal capacity. Given that the tests of direct measurement of VO 2 max needs expensive equipment, a great deal of time, and trained staff with expertise, many researchers have attempted to find indirect and si… Show more
“…VO 2 max prediction models that include the predictor variable ''age'' (Models 1, 2, 3, 4, 5 and 6) yield on the average 7.6% lower SEE's than the SEE's of the prediction models without the predictor variable ''age''. Akay, M. F., Abut, F., Kaya, K., Cetin, E. & Yarim, I. (2017).…”
Aerobic endurance describes the ability of the body’s cardio-respiratory system to perform physical activity for an extended period of time and resist fatigue. Standard tests to determine aerobic endurance involves measuring the maximum volume of oxygen (VO2max) an athlete uses up while exercising at maximal capacity. Given that the tests of direct measurement of VO2max needs expensive equipment, a great deal of time, and trained staff with expertise, many researchers have attempted to find indirect and simpler ways of predicting VO2max based on prediction equations. The aim of this study is to establish new prediction equations for estimating the VO2max from gender, age, height, weight, body mass index (BMİ), maximal heart rate (HRmax) and test time (TT) for college-aged students in Turkey. Particularly, 18 students from the College of Physical Education and Sports at Gazi University volunteered for this study. Gender has been used as a common predictor variable in all prediction models. By using different combinations of the rest of predictor variables together with the common predictor variable, twelve VO2max prediction equations have been established with the help of Multiple Linear Regression (MLR). The performance of the prediction equations have been evaluated using two well-known metrics, namely standard error of estimate (SEE) and multiple correlation coefficient (R). The results reveal that the regression equation, VO2max = - (12.331 x gender) - (0.805 x age ) + (0.883 x height) - (1.167 x weight) - (0.052 x HRmax) - (0.158 x TT) + 6.473, gave the lowest SEE (i.e3.49 mL.kg-1.min-1) and the highest R (i.e. 0.88). Application of this VO2max regression equation on an independent validation group including 6 subjects yielded an SEE of 6.24 mL.kg-1.min-1.İt can be concluded that in situations where it is difficult or even not possible to measure VO2max using exercise tests, coaches and trainers may use the given equation to predict VO2max of College of Physical Education and Sports students with acceptable error rates.
“…VO 2 max prediction models that include the predictor variable ''age'' (Models 1, 2, 3, 4, 5 and 6) yield on the average 7.6% lower SEE's than the SEE's of the prediction models without the predictor variable ''age''. Akay, M. F., Abut, F., Kaya, K., Cetin, E. & Yarim, I. (2017).…”
Aerobic endurance describes the ability of the body’s cardio-respiratory system to perform physical activity for an extended period of time and resist fatigue. Standard tests to determine aerobic endurance involves measuring the maximum volume of oxygen (VO2max) an athlete uses up while exercising at maximal capacity. Given that the tests of direct measurement of VO2max needs expensive equipment, a great deal of time, and trained staff with expertise, many researchers have attempted to find indirect and simpler ways of predicting VO2max based on prediction equations. The aim of this study is to establish new prediction equations for estimating the VO2max from gender, age, height, weight, body mass index (BMİ), maximal heart rate (HRmax) and test time (TT) for college-aged students in Turkey. Particularly, 18 students from the College of Physical Education and Sports at Gazi University volunteered for this study. Gender has been used as a common predictor variable in all prediction models. By using different combinations of the rest of predictor variables together with the common predictor variable, twelve VO2max prediction equations have been established with the help of Multiple Linear Regression (MLR). The performance of the prediction equations have been evaluated using two well-known metrics, namely standard error of estimate (SEE) and multiple correlation coefficient (R). The results reveal that the regression equation, VO2max = - (12.331 x gender) - (0.805 x age ) + (0.883 x height) - (1.167 x weight) - (0.052 x HRmax) - (0.158 x TT) + 6.473, gave the lowest SEE (i.e3.49 mL.kg-1.min-1) and the highest R (i.e. 0.88). Application of this VO2max regression equation on an independent validation group including 6 subjects yielded an SEE of 6.24 mL.kg-1.min-1.İt can be concluded that in situations where it is difficult or even not possible to measure VO2max using exercise tests, coaches and trainers may use the given equation to predict VO2max of College of Physical Education and Sports students with acceptable error rates.
This study aims to investigate the differences in locomotion characteristics according to cardiorespiratory endurance in adolescents. The subjects were 51 students in the third grade of middle school, divided into the EG group (excellent group) and NEG group (non-excellent group) according to the cardiorespiratory endurance level. This study investigates the differences in locomotion characteristics according to cardiorespiratory endurance in adolescents. We used a 20-shuttle-run for cardiorespiratory endurance level, and a 1-minute walking test was performed for each speed by applying a differential speed. Cardiorespiratory endurance variables were based on VO2 Max, and locomotion variables were analyzed by spatial-temporal parameters and foot range of motion parameters. Regarding the locomotion spatial-temporal parameters, adolescents with excellent cardiorespiratory endurance showed a more regular pattern, while foot inversion showed a more abnormal pattern. In particular, when the locomotion speed was slow, these characteristics were more clearly distinguishable. Our results confirm the characteristics of locomotion according to the growth of adolescents and can mediate the difference in walking speed to use as a primary database for the locomotion of adolescents.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.