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

You might also read

Related Articles

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

Sort by
Same author

Co-Develop-IT! Unifying Methodological Guideline for the Co-Design, Development, and Evaluation of Individually Tailored Technology-Enhanced Training and Rehabilitation Concepts: Consensus Development Study and Tutorial.

Journal of medical Internet research·2026
Same author

A machine learning model to detect falls mimicking cardiac arrest-related collapse based on wrist-derived accelerometry: the DETECT-2 study.

European heart journal. Digital health·2026
Same author

Correction: van Doorn et al. Deriving Motor States and Mobility Metrics from Gamified Augmented Reality Rehabilitation Exercises in People with Parkinson's Disease. <i>Sensors</i> 2025, <i>25</i>, 7172.

Sensors (Basel, Switzerland)·2026
Same author

The effects of gait speed on the responses to immediate and prolonged exposure to mediolateral optic flow perturbation in healthy young adults.

Human movement science·2026
Same author

A Comparison of Experimental Methods to Induce Mental Fatigue.

Perceptual and motor skills·2026
Same author

Cueing-assisted gamified augmented-reality home rehabilitation for gait and balance in people with Parkinson disease: feasibility and effectiveness in the clinical pathway.

Physical therapy·2026

Related Experiment Video

Updated: Jul 3, 2026

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings
06:21

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings

Published on: July 26, 2022

Online gait event detection using a large force platform embedded in a treadmill.

Melvyn Roerdink1, Bert H Coolen, Bert H E Clairbois

  • 1Research Institute MOVE, Faculty of Human Movement Sciences, VU University, van der Boechorststraat 9, 1081BT Amsterdam, The Netherlands. m.roerdink@fbw.vu.nl

Journal of Biomechanics
|July 29, 2008
PubMed
Summary

Accurate online detection of foot contact (FC) and foot off (FO) events is crucial for gait-dependent event control. This study demonstrates the feasibility of using a treadmill-embedded force platform for real-time gait analysis.

More Related Videos

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats
06:52

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats

Published on: April 3, 2026

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

Related Experiment Videos

Last Updated: Jul 3, 2026

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings
06:21

Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings

Published on: July 26, 2022

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats
06:52

Deep-Learning Based Multi-Joint Synchronous Tracking for Objective Quantification of Hindlimb Locomotor Kinematics in Rats

Published on: April 3, 2026

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

Area of Science:

  • Biomechanics
  • Rehabilitation Engineering
  • Human Movement Science

Background:

  • Gait research and clinical gait training can be enhanced by movement-dependent event control.
  • This requires accurate online detection of gait events like foot contact (FC) and foot off (FO).

Purpose of the Study:

  • To assess the feasibility of online FC and FO detection using a single force platform on a treadmill.
  • To evaluate the accuracy of gait parameters derived from this system compared to kinematic gold standards.

Main Methods:

  • Simultaneous recording of center-of-pressure, total force output, and kinematic data in 12 healthy participants.
  • Online detection of FC and FO events using force platform data.
  • Comparison of online gait event and parameter estimates with offline kinematic data.

Main Results:

  • Good correspondence was achieved for online FC detection compared to offline kinematic data.
  • Foot off (FO) was detected with a slight delay (31 ms).
  • Good agreement was found for spatial and temporal gait parameters, improving with refined FO estimation.

Conclusions:

  • The proposed system for online gait event detection is feasible for gait-dependent event control.
  • This technology holds promise for implementation in both gait research and clinical practice.
  • Potential applications include enhanced gait interventions and real-time feedback systems.