Correlation between EEG channels for epileptic seizure prediction
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Abstract
This paper considers correlation between EEG channels for epileptic seizure prediction. Seizure prediction is regarded as a task of classification between interictal and preictal states. Usage of correlation coefficients between EEG channels is suggested, and the effect of window length variation for correlation calculation on prediction result is investigated. Experimental database consists of intracranial electroencephalograms (iEEG) of 5 dogs and 2 humans with total duration of 678 hours. Support vector machine is used for classification. Prediction results were estimated by averaged area under ROC curve (AUC) for all patients. Correlation coefficients between channels showed high prediction performance: average AUC is in range 0,928 – 0,938 while window length varies from 10 to 180 seconds and has maximum value while 30 seconds window is used. Obtained results may be used to create and improve systems for epileptic seizure prediction. Ref. 13, figs. 2.
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