Epileptic seizures detection and the analysis of optimal seizure prediction horizon based on frequency and phase analysis

ABSTRACT: Changes in the frequency composition of the human electroencephalogram are associated with the transitions to epileptic seizures. Cross-frequency coupling (CFC) is a measure of neural oscillations in different frequency bands and brain areas, and specifically phase–amplitude coupling (PAC), a form of CFC, can be used to characterize these dynamic transitions. In this study, we propose a method for seizure detection and prediction based on frequency domain analysis and PAC combined with machine learning. We analyzed two databases, the Siena Scalp EEG database and the CHB-MIT database, and used the frequency features and modulation index (MI) for time-dependent quantification. The extracted features were fed to a random forest classifier for classification and prediction. The seizure predict

SUBMITTER: Jiang X 

PROVIDER: S-EPMC10228742 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature