A sparse representation strategy to eliminate pseudo-HFO events from intracranial EEG for seizure onset zone localization.

ABSTRACT: Objective.High-frequency oscillations (HFOs) are considered a biomarker of the epileptogenic zone in intracranial EEG recordings. However, automated HFO detectors confound true oscillations with spurious events caused by the presence of artifacts.Approach.We hypothesized that, unlike pseudo-HFOs with sharp transients or arbitrary shapes, real HFOs have a signal characteristic that can be represented using a small number of oscillatory bases. Based on this hypothesis using a sparse representation framework, this study introduces a new classification approach to distinguish true HFOs from the pseudo-events that mislead seizure onset zone (SOZ) localization. Moreover, we further classified the HFOs into ripples and fast ripples by introducing an adaptive reconstruction scheme us

SUBMITTER: Besheli BF 

PROVIDER: S-EPMC9901915 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature