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

Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

You might also read

Related Articles

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

Sort by
Same author

Spinal cord stimulation for upper limb motor function in people with chronic post-stroke hemiparesis: a feasibility trial.

Nature medicine·2026
Same author

Decompression with or without Duraplasty for Chiari I and Syringomyelia.

The New England journal of medicine·2026
Same author

Effects of peripheral nerve damage on promoting maladaptive plasticity in the spinal cord and brain.

Neuroscience·2026
Same author

Closed-loop error damping in human BCI using pre-error motor cortex activity.

bioRxiv : the preprint server for biology·2026
Same author

Temporal state-space model for forecasting slow-wave EEG power in non-human primates.

Journal of neural engineering·2026
Same author

Human auditory cortex preferentially tracks speech over music without explicit attention.

bioRxiv : the preprint server for biology·2026
Same journal

Categorization and segmentation of intestinal content frames for wireless capsule endoscopy.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same journal

An intelligent scoring system and its application to cardiac arrest prediction.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same journal

Guest editorial: Multimedia services and technologies for e-health (MUST-EH).

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same journal

Editorial: From “information technology in biomedicine” to “biomedical and health informatics”.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same journal

Equipment location in hospitals using RFID-based positioning system.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2013
Same journal

Distributed system for cognitive stimulation over interactive TV.

IEEE transactions on information technology in biomedicine : a publication of the IEEE Engineering in Medicine and Biology Society·2012
See all related articles

Related Experiment Video

Updated: May 31, 2026

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

Toward synergy-based brain-machine interfaces.

Ramana Vinjamuri1, Douglas J Weber, Zhi-Hong Mao

  • 1Department of Physical Medicine and Rehabilitation, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA. rkv3@pitt.edu

IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society
|June 29, 2011
PubMed
Summary
This summary is machine-generated.

This study shows a new brain-machine interface controlling a virtual hand using simplified movement signals. This brain-computer interface (BCI) offers intuitive control for prosthetic devices and virtual environments.

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

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
06:11

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients

Published on: April 18, 2025

Related Experiment Videos

Last Updated: May 31, 2026

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

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

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients
06:11

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients

Published on: April 18, 2025

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Robotics

Background:

  • Brain-machine interfaces (BMIs) are crucial for restoring function after neurological injury.
  • Controlling high-dimensional systems like prosthetic hands requires efficient, low-dimensional control signals.
  • Synergy-based approaches offer a promising method for simplifying complex motor control.

Purpose of the Study:

  • To demonstrate a synergy-based brain-machine interface (BMI) for controlling a high-dimensional virtual hand.
  • To investigate the use of low-dimensional command signals derived from natural hand movements.
  • To enable real-time closed-loop control of a virtual hand using electrocorticographic (ECoG) signals.

Main Methods:

  • Extracted temporal postural synergies from finger joint angular velocities during activities of daily living in healthy subjects.
  • Developed two distinct synergies: two-finger pinch and whole-hand grasp.
  • Utilized electrocorticographic (ECoG) signals from two electrodes in motor and speech areas of an epilepsy patient to control the virtual hand.
  • Implemented a real-time closed-loop control system for a 10-degrees-of-freedom virtual hand.

Main Results:

  • Successfully extracted relevant hand synergies from human movement data.
  • Demonstrated real-time control of a 10-DOF virtual hand using two distinct, low-dimensional synergies.
  • Showcased closed-loop BMI control by decoding ECoG signals to perform grasp and pinch actions on virtual objects.

Conclusions:

  • Synergy-based control is an effective strategy for simplifying complex hand movements in BMIs.
  • ECoG signals can be reliably decoded to drive low-dimensional synergies for virtual hand control.
  • This approach holds potential for developing more intuitive and functional neuroprosthetic devices.