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

Motor Unit Stimulation01:20

Motor Unit Stimulation

1.6K
When the neuron of a motor unit fires an action potential, it triggers a series of events, leading to a twitch contraction in the muscle fibers. The process of excitation-contraction coupling is crucial in relaying the action potential to the muscle fibers.
The latent period of contraction marks the onset of excitation-contraction coupling, when the action potential propagates across the sarcolemma, preparing the muscle fibers for contraction. As the fibers enter the contraction phase, the...
1.6K
Electro-mechanical Systems01:19

Electro-mechanical Systems

1.0K
Electromechanical systems are intricate configurations that effectively combine electrical and mechanical elements to achieve a desired outcome. Central to many of these systems is the DC motor, a device that converts electrical energy into mechanical motion, enabling various applications ranging from simple fans to complex robotic mechanisms.
A key component of the DC motor is the armature, a rotating circuit positioned within a magnetic field. As an electric current passes through the...
1.0K
Mechanical Systems01:22

Mechanical Systems

231
Mechanical systems are analogous to to electrical networks where springs and masses play similar roles to inductors and capacitors, respectively. A viscous damper in mechanical systems functions similarly to a resistor in electrical networks, dissipating energy. The forces acting on a mass in such systems include an applied force in the direction of motion, counteracted by forces from the spring, a viscous damper, and the mass's acceleration. This interplay of forces is mathematically...
231
PD Controller: Design01:26

PD Controller: Design

278
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
278
Feedback control systems01:26

Feedback control systems

343
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...
343
Open and closed-loop control systems01:17

Open and closed-loop control systems

802
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
802

You might also read

Related Articles

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

Sort by
Same author

A Novel Rolling Driving Principle-Enabled Linear Actuator for Bidirectional Smooth Motion.

Cyborg and bionic systems (Washington, D.C.)·2026
Same author

Knowledge-Based Deep Learning for Time-Efficient Inverse Dynamics.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society·2025
Same author

Electric field-induced alignment of Ag/Au nanowires for ultrasensitive in situ detection of Interleukin-6.

Biosensors & bioelectronics·2024
Same author

Development of a Variable-Pitch Flexible-Screw-Driven Continuum Robot (FSDCR) with Motion Decoupling Capability.

Soft robotics·2024
Same author

Gut-on-a-Chip Reveals Enhanced Peristalsis Reduces Nanoplastic-Induced Inflammation.

Small (Weinheim an der Bergstrasse, Germany)·2024
Same author

An Operating Stiffness Controller for the Medical Continuum Robot Based on Impedance Control.

Cyborg and bionic systems (Washington, D.C.)·2024

Related Experiment Video

Updated: Jul 18, 2025

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.2K

SSVEP-Based Brain-Computer Interface Controlled Robotic Platform With Velocity Modulation.

Yue Zhang, Kun Qian, Sheng Quan Xie

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |August 25, 2023
    PubMed
    Summary

    This study introduces a novel brain-computer interface (BCI) method using steady-state visual evoked potentials (SSVEPs) to control robotic arm speed via stimulus brightness. This approach enhances robotic control by allowing dynamic velocity adjustments, reducing task completion time.

    More Related Videos

    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
    10:51

    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

    Published on: March 10, 2011

    13.8K
    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

    4.4K

    Related Experiment Videos

    Last Updated: Jul 18, 2025

    SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
    11:01

    SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

    Published on: November 24, 2015

    13.2K
    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
    10:51

    An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

    Published on: March 10, 2011

    13.8K
    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

    4.4K

    Area of Science:

    • Neuroscience
    • Robotics
    • Human-Computer Interaction

    Background:

    • Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) offer non-invasive control with high data transfer rates.
    • Current SSVEP-BCIs often lack dynamic control over movement speed, limiting practical applications.
    • User control over velocity is crucial for intuitive and efficient robotic system operation.

    Purpose of the Study:

    • To develop and validate a velocity modulation method for SSVEP-based BCI control of a robotic arm.
    • To enable dynamic adjustment of robotic arm speed based on user's brain signals.
    • To improve the efficiency and user experience in SSVEP-BCI applications.

    Main Methods:

    • A stimulation interface was designed with flickers, a target, and a cursor workspace for SSVEP signal acquisition.
    • Gaussian mixture models (GMM) and Bayesian inference were used to classify flicker brightness from brain signals.
    • A brain-actuated speed function was developed, incorporating posterior probabilities and historical velocity data.

    Main Results:

    • The proposed method successfully modulated robotic arm velocity based on stimulus brightness detected via SSVEPs.
    • Online experiments demonstrated reduced reaching time in both single- and multi-target tasks.
    • The system achieved high proximity to targets, validating the effectiveness of the velocity modulation.

    Conclusions:

    • The developed SSVEP-BCI velocity modulation method offers a feasible approach for dynamic robotic arm control.
    • Stimulus brightness serves as an effective parameter for intuitive speed adjustment in BCIs.
    • This advancement has the potential to significantly enhance the usability of robotic systems controlled by brain signals.