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

You might also read

Related Articles

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

Sort by
Same author

Real-time reinforcement for human-machine interface control.

Neuron·2026
Same author

Biomechanical characteristics before, during, and after freezing of gait episodes in individuals with Parkinson's disease.

Gait & posture·2026
Same author

Decoupling simultaneous motor imagination and execution via orthogonal ECoG neural representations.

Nature communications·2026
Same author

Hand prostheses with somatosensory feedback: functional and clinical benefits.

The Lancet. Neurology·2026
Same author

Improving muscle recruitment via multi-electrode transcutaneous spinal cord stimulation using automated selectivity-driven algorithms.

APL bioengineering·2026
Same author

Editorial: Exoskeleton gait training.

Frontiers in neuroscience·2025

Related Experiment Video

Updated: May 6, 2026

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

1.9K

A brain-machine interface enables bimanual arm movements in monkeys.

Peter J Ifft1, Solaiman Shokur, Zheng Li

  • 1Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA.

Science Translational Medicine
|November 8, 2013
PubMed
Summary

Researchers developed a novel bimanual brain-machine interface (BMI) enabling monkeys to control two arms simultaneously. This advancement in BMI technology shows promise for restoring complex motor functions in paralyzed patients.

More Related Videos

Development of a Novel Task-oriented Rehabilitation Program using a Bimanual Exoskeleton Robotic Hand
06:44

Development of a Novel Task-oriented Rehabilitation Program using a Bimanual Exoskeleton Robotic Hand

Published on: May 20, 2020

6.7K
Behavioral Assessment of Manual Dexterity in Non-Human Primates
16:00

Behavioral Assessment of Manual Dexterity in Non-Human Primates

Published on: November 11, 2011

25.5K

Related Experiment Videos

Last Updated: May 6, 2026

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

1.9K
Development of a Novel Task-oriented Rehabilitation Program using a Bimanual Exoskeleton Robotic Hand
06:44

Development of a Novel Task-oriented Rehabilitation Program using a Bimanual Exoskeleton Robotic Hand

Published on: May 20, 2020

6.7K
Behavioral Assessment of Manual Dexterity in Non-Human Primates
16:00

Behavioral Assessment of Manual Dexterity in Non-Human Primates

Published on: November 11, 2011

25.5K

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Robotics

Background:

  • Brain-machine interfaces (BMIs) aim to restore motor function in paralyzed individuals.
  • Current BMIs typically allow control of only one limb at a time, limiting functional recovery.
  • Bimanual (two-arm) control presents a significant challenge for existing BMI systems.

Purpose of the Study:

  • To develop and evaluate a novel bimanual BMI system for simultaneous control of two arms.
  • To investigate the neural plasticity associated with learning bimanual BMI control.
  • To improve decoding algorithms for more intuitive and effective BMI operation.

Main Methods:

  • Recorded extracellular neural activity from 374-497 neurons in frontal and parietal cortical areas of rhesus monkeys.
  • Utilized a fifth-order unscented Kalman filter (UKF) to decode neural signals into bimanual movements.
  • Trained the UKF decoder using either a manual joystick task or passive observation of avatar arm movements.

Main Results:

  • Monkeys successfully controlled two avatar arms simultaneously using the developed bimanual BMI.
  • Decoding performance improved when representing both arms jointly in a single UKF decoder compared to separate decoders.
  • Widespread neural plasticity was observed in cortical areas with learning, including enhanced neuronal representation and dynamic changes in neural correlations.

Conclusions:

  • The developed bimanual BMI effectively enables simultaneous control of two arms, overcoming a major limitation in current technology.
  • Joint decoding of bimanual movements enhances BMI performance.
  • Learning bimanual BMI control induces significant and widespread cortical plasticity, suggesting the brain can adapt to control complex artificial limbs.