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

Evolution of the complex permittivity of biological tissue at microwaves ranges: correlation study with burn depth.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2015
See all related articles

Related Experiment Video

Updated: Aug 29, 2025

Using Electroencephalography Measurements and High-quality Video Recording for Analyzing Visual Perception of Media Content
10:41

Using Electroencephalography Measurements and High-quality Video Recording for Analyzing Visual Perception of Media Content

Published on: May 26, 2018

7.0K

Blinking characterization for each eye from EEG analysis using wavelets.

Houze Alexandre, Binczak Stephane

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |September 10, 2022
    PubMed
    Summary

    This study demonstrates that electroencephalography (EEG) can distinguish individual eye blinks from each eye. This non-invasive technique opens new possibilities for brain-computer interfaces (BCI) and biological monitoring.

    More Related Videos

    Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials
    09:40

    Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials

    Published on: November 15, 2014

    13.9K
    Classical Short-Delay Eyeblink Conditioning in One-Year-Old Children
    07:36

    Classical Short-Delay Eyeblink Conditioning in One-Year-Old Children

    Published on: September 1, 2018

    23.8K

    Related Experiment Videos

    Last Updated: Aug 29, 2025

    Using Electroencephalography Measurements and High-quality Video Recording for Analyzing Visual Perception of Media Content
    10:41

    Using Electroencephalography Measurements and High-quality Video Recording for Analyzing Visual Perception of Media Content

    Published on: May 26, 2018

    7.0K
    Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials
    09:40

    Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials

    Published on: November 15, 2014

    13.9K
    Classical Short-Delay Eyeblink Conditioning in One-Year-Old Children
    07:36

    Classical Short-Delay Eyeblink Conditioning in One-Year-Old Children

    Published on: September 1, 2018

    23.8K

    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Eye blinks are traditionally monitored using video data for tasks like drowsiness detection.
    • Advancements in brain-computer interfaces (BCI) suggest utilizing eye movements and blinks for control applications.
    • Non-invasive electroencephalography (EEG) offers a potential avenue for capturing blink-related neural signals.

    Purpose of the Study:

    • To investigate the feasibility of characterizing individual eye blinks from each eye using only EEG signals.
    • To explore the potential of dry EEG systems for accessible and portable eye blink analysis.
    • To establish a foundation for using EEG-based blink detection in BCI and monitoring systems.

    Main Methods:

    • Acquisition of non-invasive electroencephalography (EEG) data using a portable device with dry electrodes.
    • Signal processing techniques applied to EEG data to isolate and analyze eye blink events.
    • Development of algorithms to differentiate blinks originating from the left versus the right eye.

    Main Results:

    • Successful characterization of eye blinks originating from each eye independently using EEG.
    • Demonstration of the efficacy of dry EEG technology for capturing blink-related neural activity.
    • Quantification of signal features that distinguish between left and right eye blinks.

    Conclusions:

    • EEG signals, particularly from dry electrodes, are sufficient for differentiating individual eye blinks.
    • This capability enables new BCI applications and enhances biological monitoring systems.
    • Non-invasive EEG provides a viable alternative to video-based methods for eye blink analysis.