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

Matrix metalloproteinase-12 in arterial diseases: context-dependent mechanisms of vascular remodeling and therapeutic implications.

Frontiers in cardiovascular medicine·2026
Same author

Modulation of Exciton Transport in Few-Layer and Bulk Tungsten Disulfide under Hydrostatic Pressure.

Langmuir : the ACS journal of surfaces and colloids·2026
Same author

TRIM21-mediated ubiquitination of PARP1 regulated by the PI3K/AKT-STAT5A axis suppresses small cell lung cancer.

Nature communications·2026
Same author

Noise-Pressure Constrained Liutex method for robust vortex identification in 4D Flow MRI of abdominal aortic aneurysms.

Computer methods and programs in biomedicine·2026
Same author

lncRNA, miRNA, and mRNA dynamics in cholangiocyte-to-immature hepatocyte differentiation in liver regeneration.

Scientific data·2026
Same author

Microenvironment-Activated Fe-MOF Nanoplatform Enables Controlled Doxorubicin Release and Ferroptosis-Associated Oxidative Damage in MCF-7 Breast Cancer Cells.

International journal of nanomedicine·2026

Related Experiment Video

Updated: Jul 11, 2025

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
09:42

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

Published on: September 1, 2023

1.3K

EEG-Based Motor BCIs for Upper Limb Movement: Current Techniques and Future Insights.

Jiarong Wang, Luzheng Bi, Weijie Fei

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |November 6, 2023
    PubMed
    Summary

    This review covers electroencephalography (EEG)-based motor brain-computer interfaces (BCIs) for upper limb movement. It discusses current techniques and future directions for more practical neurorehabilitation and assistance applications.

    More Related Videos

    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

    445
    Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
    06:37

    Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

    Published on: July 14, 2023

    919

    Related Experiment Videos

    Last Updated: Jul 11, 2025

    Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
    09:42

    Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients

    Published on: September 1, 2023

    1.3K
    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

    445
    Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke
    06:37

    Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

    Published on: July 14, 2023

    919

    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Rehabilitation Technology

    Background:

    • Motor brain-computer interfaces (BCIs) decode brain signals for controlling external devices, bypassing peripheral nerves and muscles.
    • These BCIs are crucial for restoring, compensating, and augmenting motor function, particularly in neurorehabilitation and daily assistance for individuals with motor impairments.
    • Recent research focuses on neural signatures, movement decoding, and practical applications of motor BCIs.

    Approach:

    • This review provides a comprehensive overview of electroencephalography (EEG)-based motor BCIs, focusing specifically on upper limb movements.
    • It examines experimental paradigms, decoding techniques, and existing application systems for upper limb BCIs.
    • The review discusses challenges and future directions for developing more natural and practical motor BCIs.

    Key Points:

    • EEG-based motor BCIs offer a non-invasive method for decoding motor intentions.
    • The review highlights the importance of upper limb BCIs for functional recovery and independence.
    • Key challenges include enhancing robustness to distractions and developing multi-limb control.

    Conclusions:

    • Advancing motor BCIs requires user-centered design, improved distraction robustness, and integration of fusion techniques.
    • Future developments aim to create more natural and practical BCI systems for diverse user needs.
    • This review offers insights into the state-of-the-art and future trajectory of EEG-based upper limb motor BCIs.