Comparison of Dry and Gel Based Electrodes for P300 Brain–Computer Interfaces

Christoph Guger,Guenter Edlinger,Gunther Krausz,Brendan Z Allison

doi:10.3389/fnins.2012.00060

Christoph Guger, Guenter Edlinger + Show 2 more

Open Access

https://doi.org/10.3389/fnins.2012.00060

Copy DOI

Abstract

Most brain–computer interfaces (BCIs) rely on one of three types of signals in the electroencephalogram (EEG): P300s, steady-state visually evoked potentials, and event-related desynchronization. EEG is typically recorded non-invasively with electrodes mounted on the human scalp using conductive electrode gel for optimal impedance and data quality. The use of electrode gel entails serious problems that are especially pronounced in real-world settings when experts are not available. Some recent work has introduced dry electrode systems that do not require gel, but often introduce new problems such as comfort and signal quality. The principal goal of this study was to assess a new dry electrode BCI system in a very common task: spelling with a P300 BCI. A total of 23 subjects used a P300 BCI to spell the word “LUCAS” while receiving real-time, closed-loop feedback. The dry system yielded classification accuracies that were similar to those obtained with gel systems. All subjects completed a questionnaire after data recording, and all subjects stated that the dry system was not uncomfortable. This is the first field validation of a dry electrode P300 BCI system, and paves the way for new research and development with EEG recording systems that are much more practical and convenient in field settings than conventional systems.

Highlights

Brain–computer interfaces (BCIs) allow communication without movement
Most modern brain–computer interfaces (BCIs) rely on one of three types of mental tasks, which are associated with different types of brain activity (Wolpaw et al, 2002): Imagined movement, which produces event-related desynchronization (ERD; Guger et al, 2003; Pfurtscheller et al, 2006; Neuper et al, 2009; McFarland et al, 2010; Vidaurre et al, 2011); Attention to oscillating visual stimuli, which produces steadystate visual evoked potentials (SSVEP; Friman et al, 2007; Lin et al, 2007; Ortner et al, 2011; Allison et al, 2012); Attention to transient stimuli, which produces the P300 eventrelated potential (ERP; Sellers et al, 2006; Zhang et al, 2008; Guger et al, 2009; Townsend et al, 2010; Jin et al, 2012)
We present conventional analyses such as accuracy as well as subjective report regarding the comfort of the dry electrode system

Summary

Introduction

Brain–computer interfaces (BCIs) allow communication without movement. In a typical BCI, a user performs voluntary mental tasks that each produce distinct patterns of electrical activity in the electroencephalogram (EEG). Most modern BCIs rely on one of three types of mental tasks, which are associated with different types of brain activity (Wolpaw et al, 2002): Imagined movement, which produces event-related desynchronization (ERD; Guger et al, 2003; Pfurtscheller et al, 2006; Neuper et al, 2009; McFarland et al, 2010; Vidaurre et al, 2011); Attention to oscillating visual stimuli, which produces steadystate visual evoked potentials (SSVEP; Friman et al, 2007; Lin et al, 2007; Ortner et al, 2011; Allison et al, 2012); Attention to transient stimuli, which produces the P300 eventrelated potential (ERP; Sellers et al, 2006; Zhang et al, 2008; Guger et al, 2009; Townsend et al, 2010; Jin et al, 2012). P300 BCIs should remain prominent for at least the near future

Objectives

Methods

Results

Conclusion