Seizure signals separation using constrained topographic blind source separation

Topographic independent component analysis (TICA) is an effective tool to group the geometrically nearby source signals. The TICA algorithm further improves the results if the desired signal sources have particular properties which can be exploited in the separation process as constraints. Here the spatial-frequency information of the seizure signals is used to design a constrained TICA (CTICA) for the separation of epileptic seizure signal sources from the multichannel electroencephalogram (EEG). The results are compared with those from the TICA and the superiority of the new CTICA has been demonstrated.