01751nas a2200145   4500008004100000020002200041245009600063210006900159260004200228520117100270100001701441700002601458700002101484856010001505       2008                        eng d  a978-0-86341-934-800aPhase synchronization with ICA for epileptic seizure onset prediction in the long term EEG.0 aPhase synchronization with ICA for epileptic seizure onset predi  aSanta Margherita LigurebIETc07/20083 aThe apparently unpredictable nature of epileptic seizures can be devastating for people with epilepsy. Current medical interventions can help 75% of patients while 25% have to live with uncontrolled seizures. This motivates the search for a seizure prediction prototype using electroencephalograms (electrical signals that capture brain activity). The concept of phase synchrony has attracted much attention recently in the context of seizure prediction but is still in need of further study. The basis of our analysis is to track changes in synchrony in brain signals at and before seizure onset. The novel concept in our analysis is the use of unmixed signals as opposed to scalp EEG signals for phase synchrony analysis. The unmixing is performed by a Blind Source Separation technique called Independent component Analysis (ICA). ICA seeks underlying independent source signals from the EEG and it allows multivariate analysis using spatial as well as temporal information inherent to EEG signals. The present study on long-term continuous EEG data sets indicates that the concept of using phase synchronization with ICA may prove useful for predicting seizures.1 aGupta, Disha1 aJames, Christopher, J1 aGray, William, P  uhttp://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4609101&abstractAccess=no&userType=inst