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

Feedback control systems01:26

Feedback control systems

580
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
580

You might also read

Related Articles

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

Sort by
Same author

From autonomy to alliance: Robotic foundation models must learn with us, not just for us.

Science robotics·2026
Same author

Eccentric finger joint movements for different grip types in sport climbing.

Sports biomechanics·2026
Same author

AI in therapeutic and assistive exoskeletons and exosuits: Influences on performance and autonomy.

Science robotics·2025
Same author

Automated Evaluation of Urodynamic Examinations Through Local Linear Models: Validation on Spinal Cord Injury Individuals.

IEEE journal of translational engineering in health and medicine·2025
Same author

Accuracy Testing of Torque Limit Determination Algorithm Intended for Smart Bone Screwdrivers.

Sensors (Basel, Switzerland)·2025
Same author

Correction: Schicklin et al. Method to Generate Chlorine Dioxide Gas In Situ for Sterilization of Automated Incubators. <i>Pathogens</i> 2024, <i>13</i>, 1024.

Pathogens (Basel, Switzerland)·2025

Related Experiment Video

Updated: Dec 2, 2025

Investigating Motor Skill Learning Processes with a Robotic Manipulandum
07:52

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Published on: February 12, 2017

9.0K

When a robot teaches humans: Automated feedback selection accelerates motor learning.

Georg Rauter1,2, Nicolas Gerig3,2, Roland Sigrist3

  • 1Sensory-Motor Systems Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland. georg.rauter@unibas.ch.

Science Robotics
|November 2, 2020
PubMed
Summary

This study automated feedback selection in a robotic rowing simulator to enhance motor learning. The system individualized training, significantly improving the learning rate for trunk-arm sweep rowing compared to traditional methods.

More Related Videos

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes
04:49

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes

Published on: September 6, 2024

1.2K
Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
13:44

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Published on: August 8, 2011

14.4K

Related Experiment Videos

Last Updated: Dec 2, 2025

Investigating Motor Skill Learning Processes with a Robotic Manipulandum
07:52

Investigating Motor Skill Learning Processes with a Robotic Manipulandum

Published on: February 12, 2017

9.0K
Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes
04:49

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes

Published on: September 6, 2024

1.2K
Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy
13:44

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Published on: August 8, 2011

14.4K

Area of Science:

  • Robotics
  • Motor Learning
  • Human-Computer Interaction

Background:

  • Robotic systems are used to improve motor learning, often with adjustable feedback.
  • Automating feedback selection has been a challenge, typically requiring human trainers.
  • Previous systems lacked individualized, adaptive feedback sequences.

Purpose of the Study:

  • To automate feedback selection in a robotic rowing simulator for trunk-arm sweep rowing.
  • To investigate the impact of automated, individualized feedback on motor learning rates.
  • To demonstrate a closed-loop system for adaptive training conditions.

Main Methods:

  • Developed a robotic rowing simulator with automated feedback selection based on performance.
  • Implemented a training protocol with alternating assessment and augmented feedback sessions.
  • Compared an experimental group with individualized feedback sequences to a control group using shared sequences.

Main Results:

  • Both groups showed reductions in spatial and velocity errors.
  • The experimental group exhibited a significantly higher learning rate for the velocity profile.
  • Automated feedback selection accelerated motor learning in the rowing simulator.

Conclusions:

  • Automated feedback selection in robotic trainers can accelerate motor learning.
  • Individualized, adaptive training conditions enhance skill acquisition.
  • This closed-loop approach provides a foundation for AI-driven robotic training systems.