AUTOMATIC HIGH-FREQUENCY OSCILLATION DETECTION FROM TRIPOLAR CONCENTRIC RING ELECTRODE SCALP RECORDING

Abstract

Epilepsy is the second most prevalent neurological disorder which affects about 1% of all the humans on the earth. It has different causes and symptoms with the seizures as the main symptom. The seizures are characterized as some abnormal electrical activities of the brain. The main therapy for epilepsy is using anti-epileptic drugs which can help around 60% of the patients. The other therapy for the patients who cannot be cured by drugs is surgery. In order to define the brain tissue which is generating the seizures, there is a need to record electrical activity from the brain (electroencephalogram) with a very good signal quality. Tripolar concentric ring electrodes (TCREs) were introduced by Besio for electroencephalography (EEG) using TCREs (tEEG). The novelty of the TCRE and instrumentation is that two bipolar differential signals from three closely spaced electrode elements are recorded. Then the tripolar Laplacian derivation as a weighted sum {16*(M-D)-(O-D)} where O, M, and D are the potentials on the outer ring, middle ring, and central disc of the TCRE, respectively, is performed. We have shown that compared with conventional EEG signals, tEEG has nearly 4-fold (374%) the signal to noise ratio and less than one-tenth (8.27%) the mutual information. The goal of this work is to demonstrate that TCREs provide a unique opportunity to record high-frequency oscillations (HFOs) from scalp. To do so, a procedure was developed to process the signals making time frequency spectrograms and short time power spectrums to automatically detect HFOs. To accomplish this goal, we first make the time-frequency spectrogram and then the short time power spectrum for the whole recording. Then specify the frequency band where the narrow band high power brain activities happen and check the localized power spectrum for one second sections at this frequency to determine the time of the HFOs. Finding the HFOs and the areas of the brain generating the seizures, which is the goal of this research, can lead to very good surgical outcomes. We expect these techniques to improve diagnosis of epilepsy.