Ricerc@Sapienza

Epilepsy is a neurological disorder arising from anomalies of the electrical activity in the brain, affecting about 65 millions individuals worldwide. Objective: This work proposes a patient-specific approach for short-term prediction (i.e., within few minutes) of epileptic seizures. Methods: We use noninvasive EEG data, since the aim is exploring the possibility of developing a noninvasive monitoring/control device for the prediction of seizures. Our approach is based on finding synchronization patterns in the EEG that allow to distinguish in real time preictal from interictal states.

According to Human-System Integration analyses, cooperation between humans is one of the most relevant factors in many of today's human activities: do not take it into account in models of working environments is highly farfetched. Although the Human Factor aspects have obtained much benefit from the use of neurophysiological signals to estimate human-machine interaction, very few are the indications about neurophysiological analysis of human cooperation deviating from typical laboratory tasks.