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A Comparison of Wet-Based and Dry-Based EEG Capabilities in detecting P300 waveforms for Brain-Computer Interface Applications
  • Alessia Cacace,
  • Toby P. Breckon,
  • Jason D. Connolly*
Alessia Cacace
Department of Psychology, Durham University, UK
Author Profile
Toby P. Breckon
Departments of Computer Science | Engineering, Durham University, UK
Jason D. Connolly*
Department of Psychology, Durham University, UK

Abstract

This study compares a dry-electroencephalography (EEG) approach that does not require external shielding. This makes it amenable for a clinical EEG-based brain-computer interface (BCI) platform. A BCI forges a command relationship between the brain and a computer. We provide a direct side-by-side reference comparison of the dry-EEG methodology with a reference 64-channel wet-EEG approach. As the P300 is a robust dual polarity waveform, spanning the signal space, it works well with clinical-based BCI studies. In this study, six subjects perform a P300 auditory oddball stimulation task while we monitor the P300 with either the dry- or the wet-EEG approach. The results demonstrate the efficacy of the dry approach and we report that the approach produced all P300 components. Dry-EEG therefore performs similar to wet-EEG while providing for a less invasive, shorter set-up time and usability outside of cage shielding, all vital for everyday, home-based clinical BCI applications. Key differences for BCI researchers and future users of the approach are mentioned such that their signal processing analyses can be adjusted. Given that we induce all three primary P300 components, we conclude that this dry-EEG approach represents a highly viable P300 BCI option.