A Novel Hybrid BCI Web Browser Based on SSVEP and Eye-Tracking - Lin, Xinyuan; Malik, Wasim Q.; Zhang, Shaomin (2019 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2019)
In this study, we developed and tested assistive technology for neuro-rehabilitation consisting of a novel hybrid web browser following "true web access" principles. We combined Steady-State Visual Evoked Potentials (SSVEP) derived from electroencephalography (EEG) together with gaze-point data from an eye-tracker to provide a natural method for people with severe motor impairment to access the internet without using a computer mouse. This system was tested by three healthy subjects. All subjects completed the online experiment successfully. The results showed an average overall accuracy of 88.5 ± 1.72%, whereas the copy-spelling accuracy of 100% was achieved by every subject. The average overall ITR value was 32.2 ± 1.14 bits/min. Thanks to the joining of eye-tracking technology, our system outperformed other BCI web browsers in command detection time and information transfer rate. And the user interface is much more friendly while the control panel and webpages are highly fused together.