Le Hoa Nguyen
Dept. of Electrical Engineering, University of Science and Technology-The University of Danang

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An Experiment of Ocular Artifacts Elimination from EEG Signals using ICA and PCA Methods Turnip, Arjon; R. Setiawan, Iwan; Junaidi, Edy; Nguyen, Le Hoa
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 5, No 2 (2014)
Publisher : Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1785.199 KB) | DOI: 10.14203/j.mev.2014.v5.129-138

Abstract

In the modern world of automation, biological signals, especially Electroencephalogram (EEG) is gaining wide attention as a source of biometric information. Eye-blinks and movement of the eyeballs produce electrical signals (contaminate the EEG signals) that are collectively known as ocular artifacts. These noise signals are required to be separated from the EEG signals to obtain the accurate results. This paper reports an experiment of ocular artifacts elimination from EEG signal using blind source separation algorithm based on independent component analysis and principal component analysis. EEG signals are recorded on three conditions, which are normal conditions, closed eyes, and blinked eyes. After processing, the dominant frequency of EEG signals in the range of 12-14 Hz either on normal, closed, and blinked eyes conditions is obtained.Â