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

Exercise Stress Test01:26

Exercise Stress Test

1.9K
Introduction
Exercise stress testing, commonly known as a treadmill test, is a noninvasive procedure used to evaluate cardiovascular function and diagnose heart conditions.
Definition
An exercise stress test measures the heart's response to exertion using a treadmill or stationary bicycle. Chest electrodes record the heart's electrical activity through an ECG, and blood pressure is monitored regularly.
Purposes
1.9K
Construction of Frequency Distribution01:15

Construction of Frequency Distribution

13.2K
A frequency distribution table can be constructed using the steps given below.
First, make a table with two columns—one with the title of the data that needs to be organized, and the other column for frequency. [Draw a third column for tally marks if needed]. Then, take a look at the items given in the data set and decide if an ungrouped frequency distribution table or a grouped frequency distribution table would be more suitable. If there are large sets of different values, then it is...
13.2K

You might also read

Related Articles

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

Sort by
Same author

Evaluating a pilot nationwide licencing OSCE for internationally-qualified registered nurses: Making better decisions through mixed-methods triangulation.

Nurse education today·2026
Same author

"We might be put into situations we are uncomfortable with, but not exactly told how to deal with them": Health professional students' experiences questioning low-value care practices during work-integrated learning.

Anatomical sciences education·2025
Same author

Corrigendum to "Capsular polysaccharide structure of Acinetobacter baumannii K58 from clinical isolate MRSN31468" [Carbohydrate Res. 546 (2024) 109307].

Carbohydrate research·2025
Same author

Capsular polysaccharide structure of Acinetobacter baumannii K58 from clinical isolate MRSN31468.

Carbohydrate research·2024
Same author

Costs and economic impact of student-led clinics-A systematic review.

Medical education·2024
Same author

Breadth and visibility of children's lower limb chronic musculoskeletal pain: a scoping review.

BMJ open·2024

Related Experiment Video

Updated: Mar 26, 2026

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

13.2K

Predicting Marathon Time Using Exhaustive Graded Exercise Test in Marathon Runners.

Eloise S Till1, Stuart A Armstrong, Greg Harris

  • 11MP Sports Physicians, Mornington, Australia;2Anglesea Sports Medicine, Hamilton, New Zealand; and3Department of Physiotherapy, Monash University, Melbourne, Australia.

Journal of Strength and Conditioning Research
|January 28, 2016
PubMed
Summary

Runners can predict their marathon performance time (MPT) using a simple treadmill test. This accessible method correlates treadmill exhaustion time with race day results, aiding training and race strategy for marathon runners.

More Related Videos

Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running
06:35

Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running

Published on: September 14, 2017

9.7K
Conducting Maximal and Submaximal Endurance Exercise Testing to Measure Physiological and Biological Responses to Acute Exercise in Humans
07:26

Conducting Maximal and Submaximal Endurance Exercise Testing to Measure Physiological and Biological Responses to Acute Exercise in Humans

Published on: October 17, 2018

21.6K

Related Experiment Videos

Last Updated: Mar 26, 2026

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

13.2K
Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running
06:35

Using Gold-standard Gait Analysis Methods to Assess Experience Effects on Lower-limb Mechanics During Moderate High-heeled Jogging and Running

Published on: September 14, 2017

9.7K
Conducting Maximal and Submaximal Endurance Exercise Testing to Measure Physiological and Biological Responses to Acute Exercise in Humans
07:26

Conducting Maximal and Submaximal Endurance Exercise Testing to Measure Physiological and Biological Responses to Acute Exercise in Humans

Published on: October 17, 2018

21.6K

Area of Science:

  • Sports Science
  • Exercise Physiology
  • Running Performance Analysis

Background:

  • Marathon running is a popular endurance event with a growing participant base.
  • Accurate prediction of marathon performance time (MPT) is valuable for training and race strategy.
  • Existing prediction methods may lack accessibility or cost-effectiveness for many athletes.

Purpose of the Study:

  • To investigate the correlation between graded exercise treadmill test exhaustion time and subsequent marathon performance time (MPT).
  • To develop a simple, accessible, and cost-effective method for predicting MPT.
  • To determine if factors like sex, weekly running duration, years of running, or age influence MPT prediction.

Main Methods:

  • Recruited 59 marathon runners participating in major marathons.
  • Administered a graded exercise treadmill test to exhaustion.
  • Collected data on treadmill exhaustion time and official marathon performance time (MPT) for 42.2 km races.
  • Utilized statistical analysis to identify correlations and develop a predictive model.

Main Results:

  • A statistically significant correlation was found between treadmill exhaustion time and MPT (adjusted R(2) = 0.447).
  • Sex, weekly running duration, years of running, and age did not show a statistically significant correlation with MPT.
  • A predictive equation (y = -3.85x + 351.57) was established, where y is MPT and x is treadmill time.

Conclusions:

  • Treadmill exhaustion time is a significant predictor of marathon performance time.
  • The developed predictive model offers a simple, accessible, and cost-effective tool for athletes.
  • This method can assist the global population of marathon runners in predicting race times.