ANALISIS DATA EEG PADA PENDERITA EPILEPSI BERDASARKAN KOMPLEKSITAS DAN FASE SINKRONISASI SINYAL OTA

Epilepsy is defined as a collection of clinical symptoms and signs that arise due to impaired brain function, which occurs as a result of abnormal electrical discharges from paroxysmal neurons with various etiologies. One of the tests that help diagnose epilepsy is an electroencephalogram (EEG) signal recording. EEG is a software used in measuring the electrical activity of the outermost surface area enclosed by an electrode. Quantitative Electroencephalogram (QEEG) is a mathematical algorithm for processing EEG signal data. This study analyzed brain signals in subjects and normal subjects as controls based on signal complexity and brain synchronization signals. The test subjects consisted of three people with epilepsy and normal patients each. Data analysis methods include pre-processing to remove noise and artifacts, calculating brain signals with Sample Entropy (SampEn) and calculating brain synchronization phases using Phase Locking Value (PLV). Results Based on the analysis of the calculation of brain signals with sample entropy (SampEn), it shows that the value of normal SampEn subjects is greater than the value of SampEn subjects with epilepsy. Subjects with epilepsy experienced decreased brain signals in the occipital lobe and frontal lobe. The results of the initial subject analysis of brain signals with Phase Locking Value (PLV) showed that the normal PLV value was greater than the PLV value for epilepsy sufferers. Subjects with epilepsy experienced a decrease in the synchronization phase of brain signals in the parietal lobe, occipital lobe and frontal lobe. From the results of the analysis of calculations and brain synchronization phase, it shows that people with epilepsy experience a decrease in brain speed and synchronization signals