Real-time detection and filtering of eye movement and blink related artifacts in EEG

Eye movement related artifacts are the most significant source of noise in EEG signals. Thus, a special approach to reduction of their influence is required. However, most of currently used methods of detecting and filtering eye movement related artifacts require either an additional recording of noise signal, or are not suitable for real time applications, such as Brain-Computer Interfaces. 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.