A middle time recognition of epileptic seizures from geometrical patterns of EEG data
AbstractAn approach for middle- time recognition of epileptic seizures from EEG data is proposed. The method considers sharp changes in the recorded data using geometrical patterns of the signal in phase-space. The approach was developed using experimental clinical EEG data recorded from ten patients and reliably predicted epileptic seizures in the ten-minute interval before the seizure onsets. An estimation of sensitivity and specificity of the proposed method is also provided.
New methods in system analysis, computer science and theory of decision making