Abstract
An adaptive system for Electroencephalography (EEG) artefact rejection and Electrooculogrum (EOG) gaze estimation is proposed. The system inputs optical gaze information, and accuracy of the EOG gaze classification into an adaptive Independent Component Analysis (ICA) algorithm, for improving EEG source separation. Finally two evaluation methods based on EOG gaze estimation are suggested to assess the performance of the proposed system. The work will be of use to researchers considering using BCI and eye-tracking paradigms in real life applications. © Springer-Verlag Berlin Heidelberg 2013.
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Haji Samadi, M. R., & Cooke, N. (2013). A novel approach for adaptive EEG artefact rejection and EOG gaze estimation. In Communications in Computer and Information Science (Vol. 373, pp. 603–607). Springer Verlag. https://doi.org/10.1007/978-3-642-39473-7_120
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