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

Electrocardiogram01:29

Electrocardiogram

2.3K
An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
2.3K
Exercise Stress Test01:26

Exercise Stress Test

201
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
201
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

572
Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
572

You might also read

Related Articles

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

Sort by
Same author

Influence of military preventive policy for recruit training on COVID-19 seroconversion: the IMPACT-COVID-19 study.

BMJ military health·2025
Same author

Occupational health screening during Gurkha Central Selection: a retrospective cohort study.

BMJ military health·2024
Same author

Assessment of salivary cortisol dynamics in an infantry training exercise: a pilot study.

BMJ military health·2024
Same author

Effect of Dapagliflozin on Cardiac Function and Metabolic and Hormonal Responses to Exercise.

The Journal of clinical endocrinology and metabolism·2022
Same author

The effects of feeding and transport length on the welfare of white rhinoceroses (<i>Ceratotherium simum simum</i>) during long-distance translocations: a preliminary study.

Journal of the South African Veterinary Association·2022
Same author

The effect of water temperature on orthostatic tolerance: a randomised crossover trial.

Clinical autonomic research : official journal of the Clinical Autonomic Research Society·2022

Related Experiment Video

Updated: Jun 27, 2025

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
08:12

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions

Published on: June 5, 2019

19.9K

Do athletic ECG changes predict athletic performance in Gurkha recruits?

Michael Paton1, A K H Wong2, D Cooper3

  • 1Headquarters Army Medical Services, Camberley, UK michael.paton13@gmail.com.

BMJ Military Health
|April 30, 2024
PubMed
Summary
This summary is machine-generated.

Athletic ECG changes, like ventricular hypertrophy, show a weak link to athletic performance. The number of ECG adaptations does not predict fitness, but specific markers like T-wave inversion may indicate performance in athletes.

Keywords:
Pacing & electrophysiologyPhysiologySPORTS MEDICINE

More Related Videos

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice
04:45

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice

Published on: May 5, 2022

2.4K
Using Near-Infrared Spectroscopy Wearable Devices to Identify Central Versus Peripheral Limitations During Exercise
09:33

Using Near-Infrared Spectroscopy Wearable Devices to Identify Central Versus Peripheral Limitations During Exercise

Published on: December 19, 2024

828

Related Experiment Videos

Last Updated: Jun 27, 2025

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
08:12

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions

Published on: June 5, 2019

19.9K
Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice
04:45

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice

Published on: May 5, 2022

2.4K
Using Near-Infrared Spectroscopy Wearable Devices to Identify Central Versus Peripheral Limitations During Exercise
09:33

Using Near-Infrared Spectroscopy Wearable Devices to Identify Central Versus Peripheral Limitations During Exercise

Published on: December 19, 2024

828

Area of Science:

  • Sports Medicine
  • Cardiology
  • Exercise Physiology

Background:

  • Intensive exercise can cause electrocardiogram (ECG) changes due to increased vagal tone, ventricular wall thickness, and chamber size.
  • Understanding the relationship between these athletic ECG adaptations and actual athletic performance is crucial.

Purpose of the Study:

  • To investigate the association between ECG adaptations indicative of athleticism and athletic performance in a cohort of athletes.
  • To identify specific ECG markers that may predict or differentiate athletic performance.

Main Methods:

  • A retrospective cohort study involving 195 Nepali male recruits undergoing selection.
  • Maximal oxygen consumption (V̇O2max) was estimated using Cooper's 1.5-mile run formula.
  • Univariable and multivariable linear regression analyses were employed to correlate ECG findings with estimated V̇O2max.

Main Results:

  • No significant correlation was found between the total number of athletic ECG adaptations and estimated V̇O2max.
  • A negligible but significant correlation was observed between inferior T-wave inversion (TWI) and estimated V̇O2max (R²=0.03, p=0.02).
  • A multivariable model including right ventricular hypertrophy (RVH) voltage criteria, absence of sinus arrhythmia, T-wave axis, and inferior TWI significantly predicted estV̇O2max (R²=0.10, p=0.0004).

Conclusions:

  • Athletic ECG changes have a limited ability to predict or differentiate athletic performance in this population.
  • Voltage criteria for left ventricular hypertrophy and RVH were the most predictive ECG markers of performance.
  • Markers of increased vagal tone were not predictive, while TWI, typically a marker for disease, also indicated athletic performance in this cohort.