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 Concept Videos

Power01:08

Power

12.6K
The concept of work involves force and displacement; meanwhile, the work-energy theorem relates the net work done on a body to the difference in its kinetic energy, calculated between two points on its trajectory. While none of these quantities or relations involves time explicitly, we know that the time available to accomplish work is often just as important as the amount of work itself. For example, sprinters in a race may have achieved the same velocity at the finish, therefore,...
12.6K
Power Expended by a Constant Force00:57

Power Expended by a Constant Force

8.8K
The relationship between work done and the time taken to do it can be explained using the concept of power. For example, several sprinters in a race may have the same velocity when they reach the finish line, therefore doing the same amount of work, but the winner does it in the least amount of time. Thus, power is defined as the rate of doing work. Since work can vary as a function of time, the average power is defined as the work done during a time interval, divided by the time interval.
8.8K

You might also read

Related Articles

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

Sort by
Same author

Interlimb strength asymmetry is task-specific: moderate reliability but inconsistent limb dominance in multi-joint dynamometry.

Frontiers in sports and active living·2026
Same author

Meta-analyses in sport and exercise science: sometimes the right tool at the wrong time?

Systematic reviews·2026
Same author

Exercise Intensity but Not Cadence Affects the Dynamics of Muscle Oxygenation and Pulmonary Oxygen Uptake at the Onset of Exercise in Trained Cyclists.

International journal of sports physiology and performance·2026
Same author

Expert perspectives on Myalgic encephalomyelitis/chronic fatigue syndrome - Insights from the 3<sup>rd</sup> International Conference of the Charité Fatigue Center.

Autoimmunity reviews·2026
Same author

Acute effects of strength training interventions on subjective, neuromuscular, and biochemical fatigue parameters in elite youth soccer players.

Frontiers in sports and active living·2026
Same author

What is resistance exercise? A review of current uses and potential ways forward.

European journal of applied physiology·2026

Related Experiment Video

Updated: Dec 28, 2025

Determining and Controlling External Power Output During Regular Handrim Wheelchair Propulsion
08:55

Determining and Controlling External Power Output During Regular Handrim Wheelchair Propulsion

Published on: February 5, 2020

7.9K

Field-Derived Power-Duration Variables to Predict Cycling Time-Trial Performance.

Alfred Nimmerichter, Bernhard Prinz, Matthias Gumpenberger

    International Journal of Sports Physiology and Performance
    |February 11, 2020
    PubMed
    Summary

    Critical power (CP) and work above CP (W') accurately predict cycling performance. The inverse power-time model best predicts 20-minute time trial performance, excluding short, 1-minute trials for optimal accuracy.

    Keywords:
    critical powerfield cyclingpower–duration relationship

    More Related Videos

    Experimental Protocol of a Three-minute, All-out Arm Crank Exercise Test in Spinal-cord Injured and Able-bodied Individuals
    07:32

    Experimental Protocol of a Three-minute, All-out Arm Crank Exercise Test in Spinal-cord Injured and Able-bodied Individuals

    Published on: June 8, 2017

    10.1K
    Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test
    06:00

    Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test

    Published on: July 27, 2015

    13.0K

    Related Experiment Videos

    Last Updated: Dec 28, 2025

    Determining and Controlling External Power Output During Regular Handrim Wheelchair Propulsion
    08:55

    Determining and Controlling External Power Output During Regular Handrim Wheelchair Propulsion

    Published on: February 5, 2020

    7.9K
    Experimental Protocol of a Three-minute, All-out Arm Crank Exercise Test in Spinal-cord Injured and Able-bodied Individuals
    07:32

    Experimental Protocol of a Three-minute, All-out Arm Crank Exercise Test in Spinal-cord Injured and Able-bodied Individuals

    Published on: June 8, 2017

    10.1K
    Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test
    06:00

    Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test

    Published on: July 27, 2015

    13.0K

    Area of Science:

    • Exercise Physiology
    • Sports Science
    • Cycling Performance Analysis

    Background:

    • Critical Power (CP) and work above CP (W') are key physiological metrics for endurance athletes.
    • Accurate prediction of cycling performance, such as mean power in a 20-minute time trial (TT20), is crucial for training and competition.
    • Field-based CP and W' estimations are valuable but require validation against actual performance.

    Purpose of the Study:

    • To assess the predictive accuracy of critical power (CP) and work above CP (W') for cycling performance.
    • To compare different modeling approaches (hyperbolic, linear work/time, inverse power-time) for CP and W' estimation.
    • To determine the influence of short-duration (1-minute) prediction trials on performance prediction accuracy.

    Main Methods:

    • Ten male cyclists completed field-based 20-minute time trials (TT20) and CP/W' prediction trials of varying durations.
    • CP and W' were modeled using hyperbolic, linear work/time, and inverse power-time (INV) models.
    • Prediction accuracy was evaluated using 95% limits of agreement and a probabilistic approach.

    Main Results:

    • Excluding the 1-minute trial yielded trivial differences between predicted and actual TT20 for most models.
    • The inverse power-time (INV) model demonstrated the best individual fit (6% total error) and highest accuracy (1.3% error).
    • CP and W' derived from the INV model strongly correlated with actual TT20 (r = .975), with minimal bias (4 W).

    Conclusions:

    • Field-derived critical power (CP) and work above CP (W') provide accurate predictions of cycling performance.
    • The inverse power-time (INV) model is the most accurate method for predicting 20-minute time trial performance.
    • Short-duration (1-minute) prediction trials should be excluded from CP and W' models to avoid overestimation and improve accuracy.