Literature DB >> 23728131

Rationale and resources for teaching the mathematical modeling of athletic training and performance.

David C Clarke1, Philip F Skiba.   

Abstract

A number of professions rely on exercise prescription to improve health or athletic performance, including coaching, fitness/personal training, rehabilitation, and exercise physiology. It is therefore advisable that the professionals involved learn the various tools available for designing effective training programs. Mathematical modeling of athletic training and performance, which we henceforth call "performance modeling," is one such tool. Two models, the critical power (CP) model and the Banister impulse-response (IR) model, offer complementary information. The CP model describes the relationship between work rates and the durations for which an individual can sustain them during constant-work-rate or intermittent exercise. The IR model describes the dynamics by which an individual's performance capacity changes over time as a function of training. Both models elegantly abstract the underlying physiology, and both can accurately fit performance data, such that educating exercise practitioners in the science of performance modeling offers both pedagogical and practical benefits. In addition, performance modeling offers an avenue for introducing mathematical modeling skills to exercise physiology researchers. A principal limitation to the adoption of performance modeling is a lack of education. The goal of this report is therefore to encourage educators of exercise physiology practitioners and researchers to incorporate the science of performance modeling in their curricula and to serve as a resource to support this effort. The resources include a comprehensive review of the concepts associated with the development and use of the models, software to enable hands-on computer exercises, and strategies for teaching the models to different audiences.

Entities:  

Keywords:  Banister impulse-response model; coaching education; critical power model; exercise physiology; physical fitness

Mesh:

Year:  2013        PMID: 23728131     DOI: 10.1152/advan.00078.2011

Source DB:  PubMed          Journal:  Adv Physiol Educ        ISSN: 1043-4046            Impact factor:   2.288


  9 in total

1.  Modelling the HRV Response to Training Loads in Elite Rugby Sevens Players.

Authors:  Sean Williams; Stephen West; Dan Howells; Simon P T Kemp; Andrew A Flatt; Keith Stokes
Journal:  J Sports Sci Med       Date:  2018-08-14       Impact factor: 2.988

2.  A single-session testing protocol to determine critical power and W'.

Authors:  Keren Constantini; Surendran Sabapathy; Troy J Cross
Journal:  Eur J Appl Physiol       Date:  2014-02-22       Impact factor: 3.078

Review 3.  Relationships Between Training Load Indicators and Training Outcomes in Professional Soccer.

Authors:  Arne Jaspers; Michel S Brink; Steven G M Probst; Wouter G P Frencken; Werner F Helsen
Journal:  Sports Med       Date:  2017-03       Impact factor: 11.136

Review 4.  Development of a Revised Conceptual Framework of Physical Training for Use in Research and Practice.

Authors:  Annie C Jeffries; Samuele M Marcora; Aaron J Coutts; Lee Wallace; Alan McCall; Franco M Impellizzeri
Journal:  Sports Med       Date:  2021-09-14       Impact factor: 11.928

5.  High-intensity interval training: optimizing oxygen consumption and time to exhaustion taking advantage of the exponential reconstitution behaviour of D'.

Authors:  Filippo Vaccari; Jacopo Stafuzza; Nicola Giovanelli; Stefano Lazzer
Journal:  Eur J Appl Physiol       Date:  2022-10-15       Impact factor: 3.346

Review 6.  The Critical Power Model as a Potential Tool for Anti-doping.

Authors:  Michael J Puchowicz; Eliran Mizelman; Assaf Yogev; Michael S Koehle; Nathan E Townsend; David C Clarke
Journal:  Front Physiol       Date:  2018-06-06       Impact factor: 4.566

7.  Modelling of Running Performances: Comparisons of Power-Law, Hyperbolic, Logarithmic, and Exponential Models in Elite Endurance Runners.

Authors:  H Vandewalle
Journal:  Biomed Res Int       Date:  2018-10-03       Impact factor: 3.411

Review 8.  Power profiling and the power-duration relationship in cycling: a narrative review.

Authors:  Peter Leo; James Spragg; Tim Podlogar; Justin S Lawley; Iñigo Mujika
Journal:  Eur J Appl Physiol       Date:  2021-10-27       Impact factor: 3.078

9.  A Fitness-Fatigue Model of Performance in Peripheral Artery Disease: Predicted and Measured Effects of a Pain-Free Exercise Program.

Authors:  Nicola Lamberti; Giovanni Piva; Federico Businaro; Lorenzo Caruso; Anna Crepaldi; Pablo Jesùs Lòpez-Soto; Fabio Manfredini
Journal:  J Pers Med       Date:  2022-03-04
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.