Synchronization analysis of epilepsy data using global field synchronization

Multivariate time series analysis is of primary importance for the estimation of starting time of epilepsy seizures. Nonlinear synchronization analysis tool called Global Field Synchronization (GFS) was used to estimate the change in synchronization between the two time series. In this study, GFS is applied to the detection of epileptic seizures. Two sets of EEG data were used; first set was obtained from an unhealthy part of the brain prior to the seizure to take place (free seizure interval) and the second set obtained from the opposite healthy hemisphere of the brain. Results show a significant difference on GFS value between selected data sets, where for the unhealthy part shows a lower value of GFS than the healthy part.