Detection of EEG-Based Eye-Blinks Using A Thresholding Algorithm

In the electroencephalography (EEG) study, eye blinks are a commonly known type of ocular artifact that appears most frequently in any EEG measurement. The can be seen as spiking electrical potentials which their time-frequency properties varied across individuals. Their presence negatively impact various medical or scientific research helpful when applying to brain-computer interface applications. Hence, detecting eye-blink signals is beneficial for determining correlation between human brain and movement this paper. paper presents simple, fast, automated detection algorithm did not require user training before execution. were smoothed filtered detection. We conducted experiments with ten volunteers collected three different datasets over trials using Emotiv EPOC+ headset. proposed method performed consistently successfully detected activities mean accuracy 96%.