Quantitative determination of abrupt changes in dynamical systems: Illustration via identification of seizure termination in generalized tonic-clonic seizure EEG data

We discuss key theoretical and practical issues related to the identification of transitions in dynamical systems in real-time. We focus on the choice of candidate measures and optimization of decision thresholds for candidate measures. To illustrate these issues we develop and test a procedure for identifying one particular transition, the end-point of seizures in two-channel electroencephalographic data recorded during generalized tonic-clonic seizures. Data from twenty-eight seizures were available and used to develop and test the procedure in terms of the agreement between the computationally identified seizure end-point compared against the ratings of an expert clinical electroencephalographer. Generalizations to multivariate seizure onset detection and to seizure prediction are described.