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 Experiment Videos

Energy efficient and robust rhythmic limb movement by central pattern generators.

B W Verdaasdonk1, H F J M Koopman, F C T Van Der Helm

  • 1Department of Bio-mechanical Engineering, Faculty of Engineering Technology, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands. b.w.verdaasdonk@ctw.utwente.nl

Neural Networks : the Official Journal of the International Neural Network Society
|December 15, 2005
PubMed
Summary
This summary is machine-generated.

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

Factors associated with gym-based fitness injuries: A case-control study.

JSAMS plus·2026
Same author

What the PCSA? Addressing diversity in lower-limb musculoskeletal models: age- and sex-related differences in PCSA and muscle mass.

Journal of biomechanics·2025
Same author

Instrumented assessment of lower and upper motor neuron signs in amyotrophic lateral sclerosis using robotic manipulation: an explorative study.

Journal of neuroengineering and rehabilitation·2024
Same author

Effects of bench press technique variations on musculoskeletal shoulder loads and potential injury risk.

Frontiers in physiology·2024
Same author

Predictability of Fall Risk Assessments in Community-Dwelling Older Adults: A Scoping Review.

Sensors (Basel, Switzerland)·2023
Same author

Power in sports: A literature review on the application, assumptions, and terminology of mechanical power in sport research.

Journal of biomechanics·2018
Same journal

Q-learning based asynchronous Boolean control networks stabilization with data loss.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

New results on prescribed-time synchronization of complex networks via intermittent control.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Variance-constrained multi-view ensemble broad network for imbalanced data.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Dynamic analysis and reliable mechanical optimization application of ring HNN effected with a memristive neuron.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

DAFF-Net: A detection and search method for small-scale low surface brightness galaxies.

Neural networks : the official journal of the International Neural Network Society·2026
Same journal

Quasi-synchronization for complex networks with hybrid pinning intermittent control.

Neural networks : the official journal of the International Neural Network Society·2026
See all related articles

This study presents a mathematical model of rhythmic limb movement, revealing how tightly coupled Central Pattern Generators (CPGs) enhance energy efficiency and robustness through resonance tuning via afferent feedback.

Area of Science:

  • Neuroscience
  • Robotics
  • Biomechanics

Background:

  • Humans exhibit remarkable energy efficiency and robustness in rhythmic movements like walking.
  • Central Pattern Generators (CPGs) are neural circuits believed to underlie rhythmic motor behaviors.
  • Understanding the control mechanisms of rhythmic limb movement is crucial for both biological and artificial systems.

Purpose of the Study:

  • To present a mathematical model of rhythmic limb movement.
  • To investigate the role of Central Pattern Generators (CPGs) and afferent feedback in achieving energy efficiency and robustness.
  • To explore the applicability of these concepts in robotics.

Main Methods:

  • Development of a mathematical model for rhythmic limb movement incorporating CPGs.

Related Experiment Videos

  • Analysis of afferent feedback mechanisms, including positional and integral feedback.
  • Investigation of the impact of velocity feedback on system stability and resonance tuning.

    • Main Results:

    • Tight local coupling of CPGs to limbs contributes to energy efficiency and robustness.
    • Afferent feedback, particularly positional and integral feedback, enables resonance tuning at various frequencies.
    • Velocity feedback is essential for compensating time delays and preventing bi-stability at high frequencies.

    Conclusions:

    • The proposed CPG model explains energy-efficient and robust rhythmic limb movements.
    • The model demonstrates resonance tuning above, at, and below the CPG's endogenous frequency.
    • The findings have significant implications for the design of energy-efficient and robust robotic systems.