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.
Highlights
The brain-computer interface (BCI) technique provides a direct communication pathway between the brain and the external world by translating signals from brain activities into machine codes or commands[1]
Unlike traditional Fast Fourier Transform (FFT) algorithm to extract the features of state visual evoked potentials (SSVEP), they used canonical correlation analysis (CCA) method to match the templates of sin/cos waveform
There was no clear difference of the mean impedance. It means that the proposed dry electrodes will have similar impedance property to that of the commercial wet electrodes if they can contact with the scalp with large enough area
Summary
The brain-computer interface (BCI) technique provides a direct communication pathway between the brain and the external world by translating signals from brain activities into machine codes or commands[1]. In ref.[11], Chen et al obtained an ITR of 267 bits/min, the highest ITR to date, in a 40-target SSVEP BCI system This result was achieved by gel-based wet electrodes. In order to simplify the preparation and process of wet electrodes, many types of dry-contact electrodes have been developed They can be classified as micro-needle[12,13], tips[14,15], spring pin[16], and soft conductive polymer[17,18,19] electrodes. Mihajlovic et al.[20] used 8 metal pin-based dry electrodes to acquire SSVEPs, which could identify 4 targets with accuracy of 63% and ITR of 23 bits/min.
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