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

Muscle Coordination and Action01:24

Muscle Coordination and Action

2.1K
Muscle coordination is a complex and finely tuned process essential for smooth and purposeful movements like flexion, extension, adduction, abduction, and rotation. The human body orchestrates the actions of various muscles working in concert, each with a specific role. Four functional types describe how muscles work together: agonist, antagonist, synergist, and fixator.
Agonists
Agonist muscles, often called prime movers, are the primary muscles responsible for producing a specific movement....
2.1K
Method of Joints: Problem Solving II01:30

Method of Joints: Problem Solving II

698
Consider a truss structure with frictionless joints fixed to a wall and roller support. If a force of 150 N is applied to joint A, the forces in each member of the truss can be determined using the method of joints.
698
Development of the Limb Synovial Joints01:07

Development of the Limb Synovial Joints

1.7K
Joints form during embryonic development in conjunction with the formation and growth of the associated bones. The embryonic tissue that gives rise to all bones, cartilage, and connective tissues of the body is called mesenchyme.
The mesenchymal stem cells differentiate into chondrocytes that form the hyaline cartilage, and later the cartilaginous model of the bone. This model further transforms into a bone. This process is known as endochondral ossification.
During development, the limbs...
1.7K
Method of Joints: Problem Solving I01:30

Method of Joints: Problem Solving I

1.3K
The method of joints is a commonly used technique to analyze the forces in structural trusses. The method is based on the principle of equilibrium, which assumes that the truss members are connected by frictionless pins. The forces at each joint can be determined by considering the equilibrium of the forces acting on that joint. Consider a truss structure with two forces of 20 N and 10 N acting at joints C and D, respectively. The method of joints can be used to determine the forces FCB, FDC,...
1.3K
Introduction to Joints00:58

Introduction to Joints

3.5K
The adult human body usually has 206 bones, and except for the hyoid bone in the neck, each bone is connected to at least one other bone. Joints are the location where bones come together. Many joints allow for movement between the bones. At these joints, the articulating surfaces of the adjacent bones can move smoothly against each other. However, the bones of other joints may be joined by connective tissue or cartilage. These joints are designed for stability and provide little or no...
3.5K
Impression Management Techniques III: Aligning Actions01:29

Impression Management Techniques III: Aligning Actions

8
Aligning actions are communicative strategies individuals employ to maintain social harmony and preserve personal identity in the face of potential disruptions to social norms. These actions are particularly important in managing social impressions when one's behavior might be seen as inappropriate, incompetent, or morally questionable.Types of Aligning ActionsThe three principal types of aligning actions are disclaimers, accounts, and apologies.DisclaimersDisclaimers are preventive; they are...
8

You might also read

Related Articles

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

Sort by
Same author

Haptic interaction with a human partner for ankle training in chronic stroke: a pilot study.

Journal of neuroengineering and rehabilitation·2025
Same author

Neuro-computational modelling of closed-loop prostheses control.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Interplay of compensation and true recovery in upper limb movements post-stroke: a computational model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

From Grasping to Manipulation: Kinematic Synergy Analysis for Advanced Prosthetics.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Shadow Control of a fully modular prosthetic arm with 3-DoF Shoulder.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

A computational framework combining neuronal dynamics and evolutionary game theory for network-level synaptic interactions.

Journal of neural engineering·2025

Related Experiment Video

Updated: Sep 22, 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

Artificial Partners to Understand Joint Action: Representing Others to Develop Effective Coordination.

Cecilia De Vicariis, Giulia Pusceddu, Vinil T Chackochan

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |May 18, 2022
    PubMed
    Summary

    Researchers developed an artificial partner that learns to coordinate with humans in real-time. This artificial intelligence (AI) model improves human-machine interaction and offers insights into human-human coordination.

    More Related Videos

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    4.7K
    Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
    05:21

    Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

    Published on: January 7, 2019

    8.0K

    Related Experiment Videos

    Last Updated: Sep 22, 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
    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
    11:54

    Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

    Published on: May 8, 2021

    4.7K
    Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
    05:21

    Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses

    Published on: January 7, 2019

    8.0K

    Area of Science:

    • Robotics
    • Cognitive Science
    • Human-Computer Interaction

    Background:

    • Artificial partners offer controlled environments for studying joint action.
    • Developing AI that can effectively coordinate with humans is a key challenge.

    Purpose of the Study:

    • To present an artificial partner architecture capable of integrating human counterpart information for coordination.
    • To investigate the development of coordination strategies in human-artificial dyads.

    Main Methods:

    • An extended state observer model was used to infer human actions based on prior information, motor commands, and sensory data.
    • A joint planar task with mechanically coupled reaching movements was employed to test the artificial partner.
    • The accuracy of the artificial partner's internal representation was assessed based on mechanical coupling and sensory reliability.

    Main Results:

    • The artificial partner developed an internal representation of its human counterpart.
    • Coordination strategies in human-artificial dyads mirrored those in human-human dyads, aligning with Nash equilibria.
    • The accuracy of the internal representation was influenced by mechanical coupling and sensory information reliability.

    Conclusions:

    • The proposed artificial partner architecture effectively learns and adapts to human interaction.
    • Findings provide insights into human-human interaction mechanisms.
    • The approach has potential applications in neuro-rehabilitation and human-machine interface development.