Abstract
Recently, brain-computer interfaces (BCIs) based on visual evoked potentials (VEPs) have been shown to achieve remarkable communication speeds. As they use electroencephalography (EEG) as non-invasive method for recording neural signals, the application of gel-based EEG is time-consuming and cumbersome. In order to achieve a more user-friendly system, this work explores the usability of dry EEG electrodes with a VEP-based BCI. While the results show a high variability between subjects, they also show that communication speeds of more than 100 bit/min are possible using dry EEG electrodes. To reduce performance variability and deal with the lower signal-to-noise ratio of the dry EEG electrodes, an averaging method and a dynamic stopping method were introduced to the BCI system. Those changes were shown to improve performance significantly, leading to an average classification accuracy of 76% with an average communication speed of 46 bit/min, which is equivalent to a writing speed of 8.8 error-free letters per minute. Although the BCI system works substantially better with gel-based EEG, dry EEG electrodes are more user-friendly and still allow high-speed BCI communication.
Highlights
A Brain-Computer Interface (BCI) is a device that allows to control a computer by brain activity only, without the need for muscle control [1]
While dry electrodes haven’t been tested with a c-visual evoked potentials (VEPs) BCI system so far, the aim of this study was to test if commercially available medical-grade dry EEG electrodes can be used with a high-speed code-modulated visual evoked potentials (c-VEPs) BCI and what algorithmic improvements of the system are necessary to deal with the increased signal-to-noise ratio of dry EEG electrodes
The c-VEP BCI system used in this study is the one presented in a previous publication [4], where it is described in more detail
Summary
A Brain-Computer Interface (BCI) is a device that allows to control a computer by brain activity only, without the need for muscle control [1]. When using steady state visual evoked potentials (SSVEPs), the communication speed can further be improved by using frequency and phase information of the SSVEP to reach communication speeds up to 60 characters per minute (> 300 bit/min) [5] While these results show that VEP-based BCIs allow for high-speed communication in a lab environment, there are only few efforts to transfer those systems out of the lab and make them useable for a broader audience. One of those few approaches is the Tübingen c-VEP BCI, which was previously shown to reach spelling speeds of more than 20 error-free letters per PLOS ONE | DOI:10.1371/journal.pone.0172400. One of those few approaches is the Tübingen c-VEP BCI, which was previously shown to reach spelling speeds of more than 20 error-free letters per PLOS ONE | DOI:10.1371/journal.pone.0172400 February 22, 2017
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