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

Wearable Functional Near-Infrared Spectroscopy (fNIRS) Monitoring of Prefrontal Activation and Connectivity During Purpose-Driven Consumption.

Sensors (Basel, Switzerland)·2026
Same author

Cognitive Load Across Interaction Formats in Digital Attention Assessment for Children: Within-Subject Neuroimaging and Behavioral Comparison Study.

JMIR serious games·2026
Same author

Prediction of treatment responsiveness to home-based transcranial photobiomodulation (tPBM) intervention for cognitive decline using fNIRS concurrently recorded during tPBM.

Frontiers in aging neuroscience·2026
Same author

Functional near-infrared spectroscopy-based computer-aided diagnosis of major depressive disorder using explainable artificial intelligence: Comparison with conventional machine learning.

Journal of affective disorders·2025
Same author

Greater prefrontal cortical activation is associated with higher balance confidence in older adults.

GeroScience·2025
Same author

ERK3/MAPK6 promotes triple-negative breast cancer progression through collective migration and EMT plasticity.

Frontiers in oncology·2025

Related Experiment Video

Updated: Feb 17, 2026

Assessment and Communication for People with Disorders of Consciousness
07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

9.6K

Performance enhancement of a brain-computer interface using high-density multi-distance NIRS.

Jaeyoung Shin1, Jinuk Kwon1, Jongkwan Choi2

  • 1Department of Biomedical Engineering, Hanyang University, Seoul, Korea.

Scientific Reports
|November 30, 2017
PubMed
Summary

High-density channel configurations in functional near-infrared spectroscopy (fNIRS) do not significantly improve brain-computer interface (BCI) accuracy. However, combining multi-distance signals enhances classification performance, offering a new avenue for fNIRS-BCI development.

More Related Videos

fMRI Validation of fNIRS Measurements During a Naturalistic Task
10:36

fMRI Validation of fNIRS Measurements During a Naturalistic Task

Published on: June 15, 2015

21.6K
Qualitative and Comparative Cortical Activity Data Analyses from a Functional Near-Infrared Spectroscopy Experiment Applying Block Design
06:18

Qualitative and Comparative Cortical Activity Data Analyses from a Functional Near-Infrared Spectroscopy Experiment Applying Block Design

Published on: December 3, 2020

4.4K

Related Experiment Videos

Last Updated: Feb 17, 2026

Assessment and Communication for People with Disorders of Consciousness
07:37

Assessment and Communication for People with Disorders of Consciousness

Published on: August 1, 2017

9.6K
fMRI Validation of fNIRS Measurements During a Naturalistic Task
10:36

fMRI Validation of fNIRS Measurements During a Naturalistic Task

Published on: June 15, 2015

21.6K
Qualitative and Comparative Cortical Activity Data Analyses from a Functional Near-Infrared Spectroscopy Experiment Applying Block Design
06:18

Qualitative and Comparative Cortical Activity Data Analyses from a Functional Near-Infrared Spectroscopy Experiment Applying Block Design

Published on: December 3, 2020

4.4K

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging technique used for brain-computer interfaces (BCIs).
  • Optimizing channel configuration in fNIRS is crucial for enhancing BCI performance.
  • Multi-distance source-detector (SD) separations offer potential for deeper tissue signal analysis.

Purpose of the Study:

  • To investigate the effectiveness of high-density, multi-distance SD separations in NIRS for improving fNIRS-BCI performance.
  • To compare classification accuracy between high-density and low-density channel configurations.
  • To evaluate the impact of combining hemodynamic signals from different SD separations on BCI accuracy.

Main Methods:

  • Utilized an NIRS system with four SD separations (15, 21.2, 30, and 33.5 mm) to measure hemodynamic responses at varying depths.
  • Fifteen participants performed mental arithmetic and word chain tasks to elicit task-related hemodynamic variations.
  • Compared classification accuracy using a high-density configuration against a standard low-density configuration at 30 mm SD separation.

Main Results:

  • A high-density channel configuration alone did not yield a significant enhancement in classification accuracy.
  • Combining hemodynamic variations measured by two multi-distance SD separations significantly improved overall classification accuracy.
  • The study demonstrated that multi-distance SD separations are key to performance enhancement.

Conclusions:

  • High-density channel configurations may not be the sole factor in improving fNIRS-BCI performance.
  • The integration of hemodynamic signals from multiple distances offers a promising strategy for enhancing fNIRS-BCI accuracy.
  • This approach provides a potential new method for advancing fNIRS-BCI technology.