Quantitative Determination of Abrupt Changes in Dynamical Systems: Illustration Via Identification of Seizure Termination in Generalized Tonic–Clonic Seizure EEG Data

Abstract

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 electro-encephalographic 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.