Abstract
Artifacts related with eye movements are the most significant source of noise in EEG signals. Although there are many methods of their filtering available, most of them are not suitable for real-time applications, such as Brain-Computer Interfaces. In addition, most of those methods require an additional recording of noise signal to be provided. Applying filtering to the recorded EEG signal may unintentionally distort its uncontaminated segments. To reduce that effect filtering should be applied only to those parts of signal that were marked as artifacts. In this paper it was proven that it is possible to detect and filter those artifacts in real-time, without the need of providing an additional recording of noise signal.
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Acknowledgments
This work was supported by Polish Ministry for Science and Higher Education under internal grant BK-227/RAu1/2015/t.4 for Institute of Automatic Control, Silesian University of Technology, Gliwice, Poland.
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Binias, B., Palus, H., Jaskot, K. (2016). Real-Time Detection and Filtering of Eye Blink Related Artifacts for Brain-Computer Interface Applications. In: Gruca, A., Brachman, A., Kozielski, S., Czachórski, T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-319-23437-3_24
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DOI: https://doi.org/10.1007/978-3-319-23437-3_24
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