IEEE Transactions on Neural Systems and Rehabilitation Engineering (Jan 2022)

A Pre-Gelled EEG Electrode and Its Application in SSVEP-Based BCI

  • Weihua Pei,
  • Xiaoting Wu,
  • Xiang Zhang,
  • Aihua Zha,
  • Sen Tian,
  • Yijun Wang,
  • Xiaorong Gao

DOI
https://doi.org/10.1109/TNSRE.2022.3161989
Journal volume & issue
Vol. 30
pp. 843 – 850

Abstract

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Electroencephalogram (EEG) electrodes are critical devices for brain-computer interface and neurofeedback. A pre-gelled (PreG) electrode was developed in this paper for EEG signal acquisition with a short installation time and good comfort. A hydrogel probe was placed in advance on the Ag/AgCl electrode before wearing the EEG headband instead of a time-consuming gel injection after wearing the headband. The impedance characteristics were compared between the PreG electrode and the wet electrode. The PreG electrode and the wet electrode performed the Brain-Computer Interface (BCI) application experiment to evaluate their performance. The average impedance of the PreG electrode can be decreased to 43 $\text{k}\Omega $ or even lower, which is higher than the wet electrode with an impedance of 8 $\text{k}\Omega $ . However, there is no significant difference in classification accuracy and information transmission rate (ITR) between the PreG electrode and the wet electrode in a 40 target BCI system based on Steady State Visually Evoked Potential (SSVEP). This study validated the efficiency of the proposed PreG electrode in the SSVEP-based BCI. The proposed PreG electrode will be an excellent substitute for wet electrodes in an actual application with convenience and good comfort.

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