Extracting Blink Rate Variability from EEG Signals

TL;DR

This paper introduces a novel method for detecting blinks in EEG signals to extract blink rate variability, which can provide insights into mental processes, moving beyond traditional artifact treatment.

Contribution

It proposes a new blink detection algorithm specifically designed for EEG signals and explores its application in analyzing blink rate variability.

Findings

Successful detection of blinks in EEG recordings

Potential correlation between blink rate variability and mental states

Improved understanding of EEG artifacts

Abstract

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.