Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

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

Pain, pain catastrophizing, and autonomic nervous system dysfunction after traumatic injury: A prospective cohort study.

The journal of pain·2026

Same author

Preexisting mental disorder and mortality among people with traumatic spinal injury: a population-based retrospective cohort study.

Annals of physical and rehabilitation medicine·2026

Same author

Correction: "It has to work for us": A qualitative study exploring how lived experience engagement reframed development of a mental health module within a Spinal Cord Injury Self-Maintenance Tool.

Spinal cord·2026

Same author

"It has to work for us": A qualitative study exploring how lived experience engagement reframed development of a mental health module within a Spinal Cord Injury Self-Maintenance Tool.

Spinal cord·2026

Same author

A Wearable-Based Program to Optimise Stress Regulation, Resilience, and Wellbeing in Emergency Care Settings: A Proof-of-Concept Study Protocol.

Sensors (Basel, Switzerland)·2026

Same author

The Clinical Significance of the Manchester Colour Wheel in a Sample of People Treated for Insured Injuries.

Journal of clinical medicine·2026

Search research articles

Related Experiment Video

Updated: Jul 11, 2026

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

Analysis of eyes open, eye closed EEG signals using second-order difference plot.

Ranjit A Thuraisingham¹, Yvonne Tran, Peter Boord

¹Department of Medical and Molecular Biosciences, University of Technology, Sydney, PO Box 123, Broadway, NSW 2007, Australia.

Medical & Biological Engineering & Computing

|October 11, 2007

Summary

This study analyzed electroencephalography (EEG) signals during eyes closed (EC) and eyes open (EO) states. Results show increased EEG variability during EC, indicating potential for a novel switching mechanism in assistive technologies.

More Related Videos

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

Published on: April 26, 2024

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

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

Published on: May 26, 2018

Related Experiment Videos

Last Updated: Jul 11, 2026

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

Published on: April 26, 2024

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

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

Published on: May 26, 2018

Area of Science:

Neuroscience
Biomedical Engineering
Signal Processing

Background:

Assistive technologies enable environmental control for individuals with severe impairments.
Electroencephalography (EEG) signal analysis offers a non-invasive method for brain-computer interfaces.
Distinguishing between eyes closed (EC) and eyes open (EO) states is crucial for developing reliable control signals.

Purpose of the Study:

To investigate differences in EEG time series between EC and EO states using a signal processing technique from continuous chaotic modeling.
To assess the potential of this technique as a switching mechanism for hands-free assistive technologies.

Main Methods:

Applied a signal processing technique to analyze EEG time series data from 33 able-bodied and 17 spinal cord-injured participants.
Utilized second-order difference plots to detect EEG variability and central tendency measures for quantification.
Compared EEG signals recorded during spontaneous eyes closed (EC) and eyes open (EO) states.

Main Results:

A significant increase in EEG variability was observed during the EC state compared to the EO state.
This increased variability was localized to the O2 electrode, overlying the primary visual cortex (V1).
The findings suggest a potential replacement of coherent visual information with neural noise during the EC state.

Conclusions:

The applied signal processing technique effectively differentiates between EC and EO states based on EEG variability.
This method demonstrates potential as a continuous and reliable switching mechanism for assistive technologies.
The study highlights a novel approach for developing hands-free control systems for severely impaired individuals.