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Related Experiment Video

Updated: May 13, 2026

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

Brain-computer interfaces using capacitive measurement of visual or auditory steady-state responses.

Hyun Jae Baek¹, Hyun Seok Kim, Jeong Heo

¹Graduate Program in Bioengineering, Seoul National University, Seoul 110-799, Korea.

Journal of Neural Engineering

|March 2, 2013

Summary

This study introduces a novel capacitive electroencephalogram (EEG) electrode for brain-computer interfaces (BCIs). The new non-intrusive EEG electrode offers practical, gel-free performance for next-generation BCI applications.

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Last Updated: May 13, 2026

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Assessment and Communication for People with Disorders of Consciousness

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Visual Evoked Potential Recordings in Mice Using a Dry Non-invasive Multi-channel Scalp EEG Sensor

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Published on: January 12, 2018

Area of Science:

Neuroscience
Biomedical Engineering
Signal Processing

Background:

Current electroencephalogram (EEG) acquisition for brain-computer interfaces (BCIs) relies on wet electrodes requiring gel, preparation, and cleanup.
These limitations hinder the practical, real-world application of BCI technologies.
Next-generation BCIs need user-friendly, non-intrusive EEG platforms.

Purpose of the Study:

To develop and evaluate a novel capacitive EEG electrode as a practical alternative to conventional wet electrodes.
To assess the performance of this new electrode in brain-computer interface (BCI) systems.
To demonstrate the feasibility of gel-free, non-intrusive EEG acquisition for BCI.

Main Methods:

A new capacitive EEG electrode featuring a conductive polymer-sensing surface was designed.
Five subjects participated in experiments using steady-state visual evoked potential (SSVEP) and auditory steady-state response (ASSR) paradigms.
The capacitive electrodes were employed in both steady-state visual evoked potential (SSVEP) spelling and auditory steady-state response (ASSR) binary decision systems.

Main Results:

Offline tests showed high BCI performance with the capacitive electrodes (e.g., 95.2% accuracy, 19.91 bpm ITR for SSVEP).
Online BCI performance achieved a mean information transfer rate (ITR) of 17.78 ± 2.08 bpm for SSVEP and 0.7 ± 0.24 bpm for ASSR.
Analysis time was comparable to traditional wet electrodes, with slight increases observed.

Conclusions:

The developed capacitive EEG electrode is feasible for use in BCI systems.
This electrode offers a flexible, non-intrusive solution for future BCI applications.
The findings support the potential of capacitive electrodes for widespread BCI adoption.