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 Video

Updated: May 14, 2026

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

Model Predictive Control-Based Assist-as-Needed Strategy for Reducing Motor Slacking in Robot-Assisted

Choonggun Kim1, Youngjin Moon2, Jaesoon Choi2

  • 1Department of Mechanical Engineering, Sogang University, Seoul 04107, Republic of Korea.

Sensors (Basel, Switzerland)
|May 13, 2026
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

New Surgical Devices for Closed Reduction of Frontal Sinus Bone Fracture.

International journal for numerical methods in biomedical engineering·2025
Same author

Healthcare Experts' Advisory Unit and Support (HAUS) Program for Medical Device Development in Korea: Introduction of Clinical Unmet Needs-Based Intended Use Establishment (CLUE) Templates.

Journal of Korean medical science·2024
Same author

Methods for Clinical Evaluation of Artificial Intelligence Algorithms for Medical Diagnosis.

Radiology·2022
Same author

Bonding of Flexible Membranes for Perfusable Vascularized Networks Patch.

Tissue engineering and regenerative medicine·2021
Same author

A Vascular Intervention Assist Device Using Bi-Motional Roller Cartridge Structure and Clinical Evaluation.

Biosensors·2021
Same author

A Wi-Fi-Based Mask-Type Laryngoscope for Telediagnosis During the COVID-19 Pandemic: Instrument Validation Study.

Journal of medical Internet research·2021

This study introduces a new Assist-as-Needed (AAN) strategy for upper-limb rehabilitation robots that prevents motor slacking by optimizing robotic assistance and user participation. This model predictive control (MPC) approach enhances rehabilitation robot effectiveness.

Area of Science:

  • Robotics
  • Rehabilitation Engineering
  • Control Systems

Background:

  • Conventional Assist-as-Needed (AAN) strategies in upper-limb rehabilitation robots often mask reduced user effort due to reliance on a single error-based coefficient.
  • This lack of explicit user participation monitoring can lead to motor slacking, hindering effective rehabilitation.

Purpose of the Study:

  • To propose and validate a novel model predictive control (MPC)-based AAN strategy for upper-limb rehabilitation robots.
  • To specifically address and mitigate motor slacking by decoupling assistance and user participation.
  • To enhance the effectiveness of robot-assisted rehabilitation by promoting genuine user engagement.

Main Methods:

  • Developed a two-channel admittance structure with jointly optimized robotic-assistance gain (Ak) and user-participation-reflection gain (Bk) within a convex MPC formulation.
Keywords:
Assist-as-Neededadmittance controlhuman–robot interactionmodel predictive controlmotor slackingupper-limb rehabilitation robot

More Related Videos

Enhancing Upper Limb Function and Motor Skills Post-Stroke Through an Upper Limb Rehabilitation Robot
04:49

Enhancing Upper Limb Function and Motor Skills Post-Stroke Through an Upper Limb Rehabilitation Robot

Published on: September 6, 2024

Related Experiment Videos

Last Updated: May 14, 2026

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

Enhancing Upper Limb Function and Motor Skills Post-Stroke Through an Upper Limb Rehabilitation Robot
04:49

Enhancing Upper Limb Function and Motor Skills Post-Stroke Through an Upper Limb Rehabilitation Robot

Published on: September 6, 2024

  • Incorporated a cost function addressing trajectory tracking, participation-aware force alignment, assistance suppression, and passivity via energy-tank constraints.
  • Validated the controller through two experiments on a mobile upper-limb rehabilitation robot, including comparisons with baseline AAN methods under induced motor-slacking conditions.

    • Main Results:

    • The proposed controller demonstrated differential adaptation of Ak and Bk across varying instructed contribution levels, with participation ratios ranging from 0.103 to 0.879.
    • In motor-slacking conditions, the proposed controller achieved a significantly lower aggregate human-contribution ratio (0.282) compared to error-based (0.595) and forgetting-factor (0.535) baselines.
    • The controller explicitly represented externally imposed reductions in participation, unlike baseline methods where reductions were masked by assistive compensation.

    Conclusions:

    • The proposed MPC-based AAN strategy effectively mitigates motor slacking in upper-limb rehabilitation robots.
    • This approach enhances participation-preserving and anti-slacking capabilities in robot-assisted rehabilitation.
    • The findings suggest a more explicit and effective method for controlling robotic assistance based on user engagement.