The removal of ocular artefacts from the electroencephalogram: a review

The causes of ocular artefacts (OAs) in the human electroencephalogram (EEG) are explained and methods for their removal and their effectiveness are discussed. Recommendations for the best procedures to adopt are given together with suggestions for future research. Analogue subtraction techniques are found to be inferior to time domain techniques based on parameter estimation using the method of least squares applied to a linear function of the electro-occulograms (EOGs). Ways of assessing the effectiveness of different models for time domain removal of OAs are discussed. It is concluded that autoregressive modelling of the error terms, or else differenced data, must be used to reduce the effects of correlation in the background EEG. The most generally suitable model for the removal of random eye and blink artefacts should contain terms proportional to the right vertical EOG and the two horizontal EOGs. The EOGs should be linearly filtered to remove noise frequency components in excess of 8 Hz. Adaptive methods are preferred as on line OA removal would be desirable but for the fact that this may result in distortion of stimulus-related responses present. A number of difficulties remain and there are some suggestions for future research.

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