Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Can cycle power predict sprint running performance?

G J van Ingen Schenau1, R Jacobs, J J de Koning

  • 1Faculty of Human Movement Sciences, Free University, Amsterdam, The Netherlands.

European Journal of Applied Physiology and Occupational Physiology
|January 1, 1991
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

The effect of first and second premolar extractions on third molars: A retrospective longitudinal study.

Journal of dentistry·2017
Same author

Do Hospital Boards matter for better, safer, patient care?

Social science & medicine (1982)·2017
Same author

Rotating and translating anthropomorphic head voxel models to establish an horizontal Frankfort plane for dental CBCT Monte Carlo simulations: a dose comparison study.

Physics in medicine and biology·2016
Same author

Three-dimensional printed final occlusal splint for orthognathic surgery: design and validation.

International journal of oral and maxillofacial surgery·2016
Same author

AMPK antagonizes hepatic glucagon-stimulated cyclic AMP signalling via phosphorylation-induced activation of cyclic nucleotide phosphodiesterase 4B.

Nature communications·2016
Same author

CUSTOMISATION OF A MONTE CARLO DOSIMETRY TOOL FOR DENTAL CONE-BEAM CT SYSTEMS.

Radiation protection dosimetry·2016
Same journal

Reply to the letter by morton

European journal of applied physiology and occupational physiology·1999
Same journal

Effects of caffeine, ephedrine and their combination on time to exhaustion during high-intensity exercise.

European journal of applied physiology and occupational physiology·1999
Same journal

The effect of strength training on estimates of mitochondrial density and distribution throughout muscle fibres.

European journal of applied physiology and occupational physiology·1999
Same journal

Latency to CNS oxygen toxicity in rats as a function of PCO(2) and PO(2).

European journal of applied physiology and occupational physiology·1999
Same journal

Diurnal variations in ventilatory and cardiorespiratory responses to submaximal treadmill exercise in females.

European journal of applied physiology and occupational physiology·1999
Same journal

Comparison of cardiopulmonary responses to two types of dry-land upper-body exercise testing modes in competitive swimmers.

European journal of applied physiology and occupational physiology·1999
See all related articles

This study introduces a novel sprint running model using cycle ergometer data to accurately predict race times. It emphasizes incorporating mechanical efficiency for more realistic energetics and locomotion power equations.

Area of Science:

  • Sports Science
  • Biomechanics
  • Human Physiology

Background:

  • Current sprint running models often use competition data, limiting their accuracy.
  • A need exists for models based on controlled physiological measurements.

Purpose of the Study:

  • To develop a new model for sprint running energetics and mechanics.
  • To improve the prediction of sprint performance by avoiding competition-based parameter estimates.

Main Methods:

  • Modeled anaerobic and aerobic pathways using supra-maximal cycle ergometer data from athletes.
  • Calculated internal power losses (limb movement, air friction) from literature.
  • Developed a power equation including acceleration and submaximal cycling mechanical efficiency.
  • Solved the differential equation via simulation.

Related Experiment Videos

Main Results:

  • The model predicted realistic sprint times: 100m (10.47s), 200m (19.63s), and 400m (42.99s).
  • The simulation demonstrated the model's predictive capability for sprint distances.

Conclusions:

  • Power equations for locomotion should integrate the concept of mechanical efficiency.
  • The developed model offers a more accurate approach to sprint running analysis.