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 Experiment Videos

Brain-computer interface using a simplified functional near-infrared spectroscopy system.

Shirley M Coyle1, Tomás E Ward, Charles M Markham

  • 1National Centre for Sensor Research, Dublin City University, Glasnevin, Dublin 9, Ireland. shirley.coyle@dcu.ie

Journal of Neural Engineering
|September 18, 2007
PubMed
Summary
This summary is machine-generated.

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

Innovative Self-Powered Sensing: Potential of Fabrigami and Electrospun Nanofiber-Based Triboelectric Nanogenerator for Joint Biomechanics Monitoring.

Small (Weinheim an der Bergstrasse, Germany)·2025
Same author

A dataset of text prompts, videos and video quality metrics from generative text-to-video AI models.

Data in brief·2024
Same author

The Potential of Electrospinning to Enable the Realization of Energy-Autonomous Wearable Sensing Systems.

ACS nano·2024
Same author

Adaptive data collection for intraindividual studies affected by adherence.

Biometrical journal. Biometrische Zeitschrift·2023
Same author

Semi-Supervised Mixture Learning for Graph Neural Networks With Neighbor Dependence.

IEEE transactions on neural networks and learning systems·2023
Same author

Cognitive Performance, Quality and Quantity of Movement Reflect Psychological Symptoms in Adolescents.

Journal of sports science & medicine·2020
Same journal

Cortex-anchored sensor-space harmonics for event-related EEG.

Journal of neural engineering·2026
Same journal

Neural mechanisms of mixed speech and grasp representation in sensorimotor cortices.

Journal of neural engineering·2026
Same journal

Developing a binary communication protocol between biological neural networks using virtual white matter.

Journal of neural engineering·2026
Same journal

Spatiotemporally distinctive astrocytic and neuronal responses to repetitive intracortical microstimulation.

Journal of neural engineering·2026
Same journal

A neural mass modelling framework for evaluating EEG source localisation of seizure activity.

Journal of neural engineering·2026
Same journal

Functional and effective connectivity methods from SEEG for characterizing epileptogenic networks in refractory epilepsy: a comprehensive review and future directions.

Journal of neural engineering·2026
See all related articles

This study introduces a custom near-infrared spectroscopy (NIRS) system for brain-computer interfaces (BCIs). The functional NIRS-BCI system demonstrates potential for simple control, paving the way for further research.

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Optical Imaging

Background:

  • Brain-computer interfaces (BCIs) enable device control via thought.
  • Near-infrared spectroscopy (NIRS) is a non-invasive optical technique for measuring cortical brain activity.
  • NIRS offers safety, portability, and accessibility advantages for BCI applications.

Purpose of the Study:

  • To develop and evaluate a custom-built functional NIRS (fNIRS) system for BCI applications.
  • To investigate the feasibility of using fNIRS for motor imagery-based control.
  • To present fNIRS as an accessible and affordable alternative for BCI research.

Main Methods:

  • Construction of a custom multi-channel NIRS system.
  • Implementation of the 'Mindswitch' fNIRS-BCI application utilizing motor imagery.

Related Experiment Videos

  • Online analysis of fNIRS data with user performance feedback.
  • Main Results:

    • The fNIRS-BCI system successfully supported basic 'on/off' switching functionality.
    • Initial results indicate significant potential for fNIRS in BCI applications.
    • Performance, while currently basic, shows promise for improvement with advanced signal processing.

    Conclusions:

    • fNIRS is a viable and accessible technology for developing simple BCI systems.
    • The developed fNIRS-BCI system demonstrates potential for future advancements.
    • This work encourages further exploration and research in the fNIRS-BCI field.