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

Listening to MS: AI-assisted speech analysis for diagnosis and fatigue prediction (COMMITMENT).

Frontiers in digital health·2026

Same author

The predictive brain: Neural correlates of word expectancy align with large language model prediction probabilities.

NeuroImage·2026

Same author

Decoloniality impact assessment for AI.

AI & society·2026

Same author

LINA's testing infrastructure enables AI to take-off in unmanned aerial vehicles (UAVs).

Frontiers in robotics and AI·2026

Same author

Reopening Motor Learning Windows: Targeted Re-Engagement of Latent Pathways via Non-Invasive Neuromodulation.

Life (Basel, Switzerland)·2026

Same author

Prediction, syntax and semantic grounding in the brain and large language models.

Scientific reports·2026

Same journal

SleepConFormer: A Single-Channel EEG Framework for Sleep Staging and Consciousness Assessment in Patients with Disorders of Consciousness.

IEEE transactions on bio-medical engineering·2026

Same journal

Modeling Partial and Total Support of Left Ventricular Assist Device for Discrete Hemodynamic Control Framework.

IEEE transactions on bio-medical engineering·2026

Same journal

A Low-Cost Wearable TI-TACS Stimulator With Bipolar Quadratic-Boost Converter for Current Stimulation Validation in the Rat Brain.

IEEE transactions on bio-medical engineering·2026

Same journal

EMG-Based Gait Estimation Using Koopman-Inspired Method.

IEEE transactions on bio-medical engineering·2026

Same journal

Soft Everting Robots for Medical Applications: A Review.

IEEE transactions on bio-medical engineering·2026

Same journal

Arterial spin labeling cerebral blood flow quantification from quantitative transport mapping based on multiscale fluid mechanics simulation and deep learning.

IEEE transactions on bio-medical engineering·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 21, 2026

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

Quantifying electrode reliability during brain-computer interface operation.

Hesam Sagha, Serafeim Perdikis, José del R Millán

IEEE Transactions on Bio-Medical Engineering

|November 7, 2014

Summary

This summary is machine-generated.

This study introduces two novel metrics to detect anomalous signals in noninvasive brain-computer interface (BCI) applications. These metrics quantify electrode reliability in real-time, aiming to improve BCI performance by identifying signal degradation.

More Related Videos

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

Published on: July 7, 2023

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

Related Experiment Videos

Last Updated: Apr 21, 2026

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Utilizing Electroencephalography Measurements for Comparison of Task-Specific Neural Efficiencies: Spatial Intelligence Tasks

Published on: August 9, 2016

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

Published on: July 7, 2023

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Recording Human Electrocorticographic ECoG Signals for Neuroscientific Research and Real-time Functional Cortical Mapping

Published on: June 26, 2012

Area of Science:

Neuroscience
Biomedical Engineering
Signal Processing

Background:

Noninvasive brain-computer interfaces (BCIs) can suffer performance degradation due to unexpected signal anomalies.
Continuous monitoring of raw signals is often lacking, making it difficult to detect issues like electrode misplacement or connectivity loss during operation.

Purpose of the Study:

To develop and evaluate metrics for real-time assessment of electrode reliability in BCI systems.
To quantify channel deviation from expected behavior to identify signal degradation.

Main Methods:

Proposed two novel metrics to detect deviations in individual electrode channels.
Assessed metric effectiveness through experiments involving electrode swaps, manipulation, and artificially degraded P300 signals.

Main Results:

The proposed metrics effectively quantify signal degradation at the channel level.
Demonstrated the ability of metrics to detect anomalies arising from various sources like electrode issues.

Conclusions:

The developed metrics can be integrated into BCI systems for online monitoring of electrode reliability.
Real-time quantification of electrode reliability can enhance BCI performance and robustness.