  Generally, blinks are treated on equal with artifacts and noise while
analyzing EEG signals. However, blinks carry important information about mental
processes and thus it is important to detect blinks accurately. The aim of the
presented study is to propose a blink detection method and discuss its
application for extracting blink rate variability, a novel concept that might
shed some light on the mental processes. In this study, 14 EEG recordings were
selected for assessing the quality of the proposed blink detection algorithm.
