Applying time frequency analysis to seizure EEG activity

BLANCO, S; SALGADO, P; KOCHEN, S; ROSSO, OSVALDO ANÍBAL; SILVIA KOCHEN

IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE

Año: 1997 p. 64 - 71

0739-5175

The authors confirmed previous results about the ability to perform an EEG time-frequency analysis in a systematic way. This method gives an accurate description of the time evolution of the rhythm defined in the epileptic activity. One can generate a time series that quantifies the dynamic behavior of brain activity, independent of the EEG signal morphology. In particular, the lag correlation among these new time series gives a good picture of the information transfer process of epileptiform activity throughout the brain. The authors applied this method to intracranial EEG records of epileptic refractory patients. They conclude that the epileptic seizure could be characterized by a quasi-monofrequency activity for some of the bands. This characteristic can be used to analyze the epileptic seizure and to study the dynamic changes in its time evolution. The use of the present time-frequency analysis, together with patient clinical history and the visual assessment of the EEG, can contribute to the identification of the source of epileptic seizure activity and of its propagation within the brain. Furthermore, it yields new insights with respect to the behavior of the electrical activity during the seizure The authors confirmed previous results about the ability to perform an EEG time-frequency analysis in a systematic way. This method gives an accurate description of the time evolution of the rhythm defined in the epileptic activity. One can generate a time series that quantifies the dynamic behavior of brain activity, independent of the EEG signal morphology. In particular, the lag correlation among these new time series gives a good picture of the information transfer process of epileptiform activity throughout the brain. The authors applied this method to intracranial EEG records of epileptic refractory patients. They conclude that the epileptic seizure could be characterized by a quasi-monofrequency activity for some of the bands. This characteristic can be used to analyze the epileptic seizure and to study the dynamic changes in its time evolution. The use of the present time-frequency analysis, together with patient clinical history and the visual assessment of the EEG, can contribute to the identification of the source of epileptic seizure activity and of its propagation within the brain. Furthermore, it yields new insights with respect to the behavior of the electrical activity during the seizure