Time in human endurance models. From empirical models to physiological models.
نویسندگان
چکیده
This article traces the study of interrelationships between power output, work done, velocity maintained or distance covered and the endurance time taken to achieve that objective. During the first half of the twentieth century, scientists examined world running records for distances from < 100 m to > 1000 km. Such examinations were empirical in nature, involving mainly graphical and crude curve-fitting techniques. These and later studies developed the use of distance/time or power/time models and attempted to use the parameters of these models to characterise the endurance capabilities of athletes. More recently, physiologists have proposed theoretical models based on the bioenergetic characteristics of humans (i.e. maximal power, maximal aerobic and anaerobic capacity and the control dynamics of the system). These models have become increasingly complex but they do not provide sound physiological and mathematical descriptions of the human bioenergetic system and its observed performance ability. Finally, we are able to propose new parameters that can be integrated into the modelling of the power/time relationship to explain the variability in endurance time limit at the same relative exercise power (e.g. 100% maximal oxygen uptake).
منابع مشابه
Which Methodology is Better for Combining Linear and Nonlinear Models for Time Series Forecasting?
Both theoretical and empirical findings have suggested that combining different models can be an effective way to improve the predictive performance of each individual model. It is especially occurred when the models in the ensemble are quite different. Hybrid techniques that decompose a time series into its linear and nonlinear components are one of the most important kinds of the hybrid model...
متن کاملAN EXTENDED FUZZY ARTIFICIAL NEURAL NETWORKS MODEL FOR TIME SERIES FORECASTING
Improving time series forecastingaccuracy is an important yet often difficult task.Both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. In this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...
متن کاملEating Time Modulations of Physiology and Health: Life Lessons from Human and Ruminant Models
Tissue nutrient supply may be synchronized with endogenous physiological rhythms to optimize animal and human health. Glucose tolerance and insulin sensitivity have endogenous rhythms that are not essentially dependent on food type and eating. Human glucose tolerance declines as day comes into night. Based on such evolutionary findings, large evening meals must be avoided to reduce risks of vis...
متن کاملEstimation of Global Solar Irradiance Using a Novel combination of Ant Colony Optimization and Empirical Models
In this paper, a novel approach for the estimation of global solar irradiance is proposed based on a combination of empirical correlation and ant colony optimization. Empirical correlation has been used to estimate monthly average of daily global solar irradiance on a horizontal surface. The Ant Colony Optimization (ACO) algorithm has been applied as a swarm-intelligence technique to tune the c...
متن کاملPerformance Evaluation of Dynamic Modulus Predictive Models for Asphalt Mixtures
Dynamic modulus characterizes the viscoelastic behavior of asphalt materials and is the most important input parameter for design and rehabilitation of flexible pavements using Mechanistic–Empirical Pavement Design Guide (MEPDG). Laboratory determination of dynamic modulus is very expensive and time consuming. To overcome this challenge, several predictive models were developed to determine dyn...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Sports medicine
دوره 27 6 شماره
صفحات -
تاریخ انتشار 1999