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

Development and validation of a kinematic hindlimb cycling model for rats.

Scientific reports·2025
Same author

ARISE Control of an Uncertain Lower-Limb Hybrid Exoskeleton.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]·2025
Same author

Accelerated Gradient Approach For Deep Neural Network-Based Adaptive Control of Unknown Nonlinear Systems.

IEEE transactions on neural networks and learning systems·2024
Same author

Encouraging Volitional Pedaling in Functional Electrical Stimulation-Assisted Cycling Using Barrier Functions.

Frontiers in robotics and AI·2021
Same author

Electromechanical delay during functional electrical stimulation induced cycling is a function of lower limb position.

Disability and rehabilitation. Assistive technology·2021
Same author

Characterization of the Time-Varying Nature of Electromechanical Delay During FES-Cycling.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2020
Same journal

Ultrasound-Informed State Estimation of Wrist Tremor Dynamics via Koopman Operator for Personalized Sensory Peripheral Nerve Stimulation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same journal

Motion Intention Recognition and DDPG-Based Adaptive Impedance Control for a Robotic Upper-Limb Exoskeleton.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same journal

CNN-Based Modelling Reveals Temporal Brain Dynamics of Auditory Intensity Processing.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same journal

Pathology-Informed Augmentation Improves Cross-Cohort IMU-to-vGRF Estimation Between Healthy Adults and Adults With Osteoarthritis.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same journal

Effects of task-driven head orientations on gait and balance during walking in virtual reality.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
Same journal

Wearable sensor-based Mild Cognitive Impairment Identification: A Multi-Domain Gait Analysis Approach with Association Rule Mining.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2026
See all related articles

Related Experiment Video

Updated: Aug 29, 2025

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
06:58

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Published on: November 6, 2015

9.6K

Data-Based and Opportunistic Integral Concurrent Learning for Adaptive Trajectory Tracking During Switched

Brendon C Allen, Kimberly J Stubbs, Warren E Dixon

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |September 5, 2022
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces adaptive integral concurrent learning (ICL) controllers for hybrid exoskeletons, enhancing rehabilitation for movement disorders by learning uncertain dynamics and functional electrical stimulation (FES) parameters for improved trajectory tracking.

    More Related Videos

    A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning
    11:32

    A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning

    Published on: January 19, 2022

    3.5K
    Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks
    11:31

    Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks

    Published on: December 5, 2014

    15.3K

    Related Experiment Videos

    Last Updated: Aug 29, 2025

    A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study
    06:58

    A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

    Published on: November 6, 2015

    9.6K
    A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning
    11:32

    A Flexible Platform for Monitoring Cerebellum-Dependent Sensory Associative Learning

    Published on: January 19, 2022

    3.5K
    Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks
    11:31

    Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks

    Published on: December 5, 2014

    15.3K

    Area of Science:

    • Robotics
    • Biomedical Engineering
    • Control Systems

    Background:

    • Hybrid exoskeletons combining functional electrical stimulation (FES) and motorized systems offer rehabilitation potential for movement disorders.
    • These systems face challenges due to nonlinear dynamics, mode switching, and uncertain muscle control effectiveness from FES.
    • Accurate control is crucial for effective rehabilitation but complicated by these inherent uncertainties.

    Purpose of the Study:

    • To develop adaptive integral concurrent learning (ICL) controllers for a hybrid biceps curl exoskeleton.
    • To enable opportunistic, data-driven learning of uncertain human and electromechanical parameters during exoskeleton operation.
    • To address challenges posed by unknown motor effectiveness and FES electrode switching for fatigue reduction.

    Main Methods:

    • Development of adaptive integral concurrent learning (ICL) motor and FES controllers.
    • Utilizing Lyapunov-based stability analysis to prove global exponential trajectory tracking and parameter estimation error convergence.
    • Implementing FES with switching electrodes on the biceps brachii to manage fatigue and adapt to different dynamic subsystems.

    Main Results:

    • The developed ICL controllers demonstrated effective learning of uncertain parameters across different active subsystems (motor and FES electrodes).
    • Experimental validation on twelve healthy participants showed low average position tracking errors: 0.28 ± 3.53 degrees across all trials.
    • The controllers successfully managed the complexities of switching FES electrodes and unknown motor dynamics.

    Conclusions:

    • Adaptive ICL controllers provide a robust solution for controlling hybrid exoskeletons with uncertain dynamics and FES.
    • This approach enhances trajectory tracking and parameter learning, paving the way for improved exoskeleton-assisted rehabilitation.
    • The findings support the potential of intelligent control strategies for advanced assistive and rehabilitative robotic devices.