Determination of Ocular Artifacts in the Clinical EEG Software by a Peripheral Device

Andrzej Biedka,Joanna Górecka

doi:10.3390/electronics10020108

Abstract

The occurrence of physiological artifacts generated by eye movements in electrical brain activity (electroencephalography, EEG) is a well-known problem in clinical practice. In order to increase the accuracy of the detection of eye movements during EEG examination, additional electrooculogram channels (electrooculography, EOG) with a standard PC keyboard are used. The EOG technique is not always comfortable for patients. Another issue is that the use of EOG channels in the EEG examination leads to the prolongation of time required for patient preparation. To solve these problems, we developed a new peripheral device suitable for the indication of common ocular artifacts in EEG. The obtained differences between the recommended methods (i.e., EOG, PC keyboard) and our new device have been presented using RMSE (root mean square error). The presented equipment can be used either during EEG examination or after registration of EEG signals in order to indicate the ocular artifacts. Furthermore, this device is compatible with the EEG software used in clinical practice.

Highlights

In spontaneous electroencephalogram signals (EEG data) of healthy adults, eye movements or blinking are the most common source of physiological artifacts
The use of EOG electrodes during EEG registration is recommended for better identification of noncerebral components
It should be mentioned that the ocular artifacts such as eye movement or blinks artifacts occur in the delta range 0–4 Hz [3] [5]

Summary

Introduction

In spontaneous electroencephalogram signals (EEG data) of healthy adults, eye movements (i.e., eyes open and closed, look up and down, look right and left) or blinking are the most common source of physiological artifacts. The amplitude of the ocular artifacts is much higher than the amplitude of EEG signals and depends on the type of eye movements and the patient health status. In the case of healthy subjects between the ages of 20 and 60 years, it usually does not exceed 300 mV, with the maximum at the pre-frontal region of the head, and decreases with the distance from the EOG channels [3] The main problem with the analysis of EEG data is a proper detection of the EOG artifacts in EEGs, because some of them are very similar to the brain signals [3] The main problem with the analysis of EEG data is a proper detection of the EOG artifacts in EEGs, because some of them are very similar to the brain signals [3] (pp. 169–195) [5] (pp. 107–117)

Methods

Results

Conclusion