Ocular artifact, namely eye-blink is an inevitable and one of the most destructive noises EEG signals. Many solutions detecting artifact were proposed. Different subsets features Machine Learning (ML) classifiers used for this purpose. But no comprehensive comparison these ML was presented. This paper presents twelve five classifiers, commonly in existing studies detection artifacts. An dataset...

this study investigates the detection of the drowsiness state for a future application such as in the reduction ofthe road traffic accidents. the electroencephalography(eeg), electrooculography (eog), driving quality (dq), and karolinska sleepiness scale (kss) data of 7 male during approximately 20 hours of sleep deprivation were recorded. to reduce the eye blink artifact, an automatic mechanis...

A novel blind signal extraction (BSE) scheme for the removal of eye-blink artifact from electroencephalogram (EEG) signals is proposed. In this method, in order to remove the artifact, the source extraction algorithm is provided with an estimation of the column of the mixing matrix corresponding to the point source eye-blink artifact. The eye-blink source is first extracted and then cleaned, ar...

Introduction: Nowadays, excessive computer use in the workplace has raised concerns about the health status of VDT workers, particularly complaints about eye discomforts. Due to the importance of the eyelids and eye closure parameters on eye health during computer works and the direct effect of monitor height on these parameters, this study was aimed to examine the effect of different monitor h...

In the modern world of automation, biological signals, especially Electroencephalogram (EEG) and Electrocardiogram (ECG), are gaining wide attention as a source of biometric information. Earlier studies have shown that EEG and ECG show versatility with individuals and every individual has distinct EEG and ECG spectrum. EEG (which can be recorded from the scalp due to the effect of millions of n...

In this paper we proposed a technique to remove eye blink artifact from electroencephalogram (EEG) using lifting wavelet transform (LWT). The LWT has been successfully used in eye blink artifact suppression form the recorded electroencephalography (EEG) signals using a data-adaptive subband filtering approach. The LWT is applied to decompose EEG signal into a finite set of subbands. The energy ...

Electrooculography (EOG) signal is one of the useful biomedical signals. Development of EOG signal as a control signal has been paid more increasing interest in the last decade. In this study, we are proposing a robust classification algorithm of eight useful directional movements that it can avoid effect of noises, particularly eye-blink artifact. Threshold analysis is used to detect onset of ...

Eye blink artifact is one of the major problems in electroencephalograph (EEG) signals which mainly affected a frontal channel. A frontal channel often involved in recent applications of portable EEG devices which require a real time processing including for artifact removal. In this paper, we proposed a new referencing method in adaptive filtering for eye blinks removal of a single-channel EEG...

Eye blink is an important and inevitable artifact during scalp electroencephalogram (EEG) recording. The main problem in EEG signal processing is how to identify eye blink components automatically with independent component analysis (ICA). Taking into account the fact that the eye blink as an external source has a higher sum of correlation with frontal EEG channels than all other sources due to...

Neural correlates of eye blink in healthy human subjects can be investigated using functional magnetic resonance imaging. However, the focus of most previous studies has been on intentional eye blinking. The goal of the present study was to examine the neural correlates of spontaneous eye blinking with the help of EOG measurements during data acquisition of fMRI. After the removal of the pulse ...