A High-Speed SSVEP-Based BCI Using Dry EEG Electrodes

Xiao Xing, Yijun Wang*, Weihua Pei, Xuhong Guo, Zhiduo Liu, Fei Wang, Gege Ming, Hongze Zhao, Qiang Gui, Hongda Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

93 Citations (Scopus)

Abstract

A high-speed steady-state visual evoked potentials (SSVEP)-based brain-computer interface (BCI) system using dry EEG electrodes was demonstrated in this study. The dry electrode was fabricated in our laboratory. It was designed as claw-like structure with a diameter of 14 mm, featuring 8 small fingers of 6 mm length and 2 mm diameter. The structure and elasticity can help the fingers pass through the hair and contact the scalp when the electrode is placed on head. The electrode was capable of recording spontaneous EEG and evoked brain activities such as SSVEP with high signal-to-noise ratio. This study implemented a twelve-class SSVEP-based BCI system with eight electrodes embedded in a headband. Subjects also completed a comfort level questionnaire with the dry electrodes. Using a preprocessing algorithm of filter bank analysis (FBA) and a classification algorithm based on task-related component analysis (TRCA), the average classification accuracy of eleven participants was 93.2% using 1-second-long SSVEPs, leading to an average information transfer rate (ITR) of 92.35 bits/min. All subjects did not report obvious discomfort with the dry electrodes. This result represented the highest communication speed in the dry-electrode based BCI systems. The proposed system could provide a comfortable user experience and a stable control method for developing practical BCIs.

Original languageEnglish
Article number14708
JournalScientific Reports
Volume8
Issue number1
DOIs
Publication statusPublished - 1 Dec 2018
Externally publishedYes

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