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

Variability: Analysis01:11

Variability: Analysis

143
Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
143
Variation in Acceleration due to Gravity near the Earth's Surface01:20

Variation in Acceleration due to Gravity near the Earth's Surface

2.4K
An object's apparent weight is its weight measured by a spring balance at its location. It is different from its true weight, the force with which the Earth pulls it, because of the Earth's rotation. Mathematically, an object's apparent weight equals its true weight minus the centripetal force that keeps it in a circular motion along with the Earth's surface every 24 hours.
The difference between the true and apparent weights is proportional to the square of the Earth's...
2.4K

You might also read

Related Articles

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

Sort by
Same author

Combined FIFA 11+  Kids and Neuromuscular Training Effects in Youth Soccer Players.

International journal of sports medicine·2026
Same author

Differential Time-of-Day Effects of Caffeine Capsule and Mouth Rinse on Physical Performance and Volleyball-Specific Skills in Adolescent Male Volleyball Players.

Nutrients·2026
Same author

Back squat and deadlift fatiguing protocols elicit distinct countermovement jump profiles: phase-specific predictors and soreness responses.

British medical bulletin·2026
Same author

Cigarette smoking slows the on- and the off- cardiorespiratory and gas-exchange kinetics during moderate exercise in young, physically active adults.

European journal of applied physiology·2026
Same author

Artificial intelligence-generated marathon training programs: reliable tools in exercise prescription for athletic performance?

British medical bulletin·2026
Same author

Which Criteria Are Used to Clear Athletes to Return to Sport After Achilles Tendon Repair? A Scoping Review.

Sports health·2026

Related Experiment Video

Updated: Jul 10, 2025

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
08:56

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

Published on: November 7, 2014

13.9K

Gait Variability at Different Walking Speeds.

Johnny Padulo1, Susanna Rampichini1, Marta Borrelli1

  • 1Department of Biomedical Sciences for Health (SCIBIS), Università degli Studi di Milano, 20133 Milan, Italy.

Journal of Functional Morphology and Kinesiology
|November 21, 2023
PubMed
Summary
This summary is machine-generated.

Gait variability (GV) is most effective at self-selected walking speeds (SS), indicating optimal walking control. This study found that SS provides a reliable method for assessing gait adjustments and normalizing walking intensity.

Keywords:
gait analysishuman locomotionkinematic analysisphysiological responsesymmetry

More Related Videos

Lower-Limb Biomechanical Characteristics Associated with Unplanned Gait Termination Under Different Walking Speeds
05:52

Lower-Limb Biomechanical Characteristics Associated with Unplanned Gait Termination Under Different Walking Speeds

Published on: August 25, 2020

4.6K
Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
10:52

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

8.8K

Related Experiment Videos

Last Updated: Jul 10, 2025

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults
08:56

Clinical Assessment of Spatiotemporal Gait Parameters in Patients and Older Adults

Published on: November 7, 2014

13.9K
Lower-Limb Biomechanical Characteristics Associated with Unplanned Gait Termination Under Different Walking Speeds
05:52

Lower-Limb Biomechanical Characteristics Associated with Unplanned Gait Termination Under Different Walking Speeds

Published on: August 25, 2020

4.6K
Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
10:52

Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior

Published on: April 13, 2016

8.8K

Area of Science:

  • Biomechanics
  • Human Movement Science
  • Sports Medicine

Background:

  • Gait variability (GV) reflects inconsistencies in muscular activity and body movements during locomotion.
  • GV is a sensitive indicator for quantifying adjustments in walking control.
  • Understanding the relationship between GV and walking speed is crucial for optimizing gait analysis and bilateral coordination.

Purpose of the Study:

  • To investigate the association between gait variability (GV) and different walking speeds.
  • To determine if self-selected walking speed (SS) offers a more effective measure of gait control compared to other speeds.
  • To explore the potential of SS as a standardized approach for gait analysis.

Main Methods:

  • Fourteen male students participated, walking 1 km daily for three days at their self-selected speed (SS).
  • Participants then underwent treadmill testing at three speeds: SS-20%, SS, and SS+20%, with kinematic data collected.
  • Measures included heart rate (HR), rate of perceived exertion (RPE), contact time (CT), swing time (ST), stride length (SL), stride cycle (SC), and Phase Coordination Index (PCI) for GV.

Main Results:

  • RPE and HR increased significantly with higher walking speeds.
  • Contact time (CT) and stride cycle (SC) decreased, while stride length (SL) increased as walking speed increased.
  • Phase Coordination Index (PCI), representing gait variability, was lowest (indicating most effective control) at self-selected speed (SS).

Conclusions:

  • Walking speed significantly influences kinematic variables and metabolic demand.
  • Self-selected walking speed (SS) demonstrates the most effective gait variability, suggesting optimal walking control.
  • SS represents a promising methodological approach for normalizing walking intensity and assessing gait patterns accurately.