Recently an independent component analysis (ICA) becomes powerful tools to processing bio-signals. In our studies, the ICA is applied to processing on saccade-related EEG signals in order to predict saccadic eye movements because an ensemble averaging, which is a conventional processing method of EEG signals, is not suitable for real-time processing. We have already detected saccade-related independent components (ICs) by ICA. However, features of saccade-related EEG signals and saccade-related ICs were not compared. In this paper, saccade-related EEG signals and saccade-related ICs in visually and auditorily guided saccade task are compared in the point of the latency between starting time of a saccade and time when a saccade-related EEG signal or an IC has maximum value and in the point of the peak scale where a saccade-related EEG signal or an IC has maximum value. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Funase, A., Tohru, Y., Mouri, M., Barros, A. K., Cichocki, A., & Takumi, I. (2006). Analysis on EEG signals in visually and auditorily guided saccade task by FICAR. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3889 LNCS, pp. 438–445). https://doi.org/10.1007/11679363_55
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