Automatic Reduction of Artifacts in EEG-Signals

Electroencephalograms (EEG) are often contaminated with high amplitude artifacts limiting the usability of data. Methods that reduce these artifacts are often restricted to certain types of artifacts, require manual interaction or large training data sets. Within this paper we introduce a novel method, which is able to eliminate many different types of artifacts without manual intervention. The algorithm first decomposes the signal into different sub-band signals in order to isolate different types of artifacts into specific frequency bands. After signal decomposition with principal component analysis (PCA) an adaptive threshold is applied to eliminate components with high variance corresponding to the dominant artifact activity. Our results show that the algorithm is able to significantly reduce artifacts while preserving the EEG activity. Parameters for the algorithm do not have to be identified for every patient individually making the method a good candidate for preprocessing in automatic seizure detection and prediction algorithms.

Detection of regional blood perfusion changes in epileptic seizures with dynamic brain perfusion CT--a pilot study

BACKGROUND AND PURPOSE: Perfusion CT (P-CT) is used for acute stroke management, not, however, for evaluating epilepsy. To test the hypothesis that P-CT may identify patients with increased regional cerebral blood flow during subtle status epilepticus (SSE), we compared P-CT in SSE to different postictal conditions. METHODS: Fifteen patients (mean age 47 years, range 21-74) underwent P-CT immediately after evaluation in our emergency room. Asymmetry indices between affected and unaffected hemispheres were calculated for regional cerebral blood volume (rCBV), regional cerebral blood flow (rCBF), and mean transit time (MTT). Regional perfusion changes were compared to EEG findings. RESULTS: Three patients in subtle status epilepticus (group 1) had increased regional perfusion with electro-clinical correlate. Six patients showed postictal slowing on EEG corresponding to an area of regional hypoperfusion (group 2). CT and EEG were normal in six patients with a first epileptic seizure (group 3). Cluster analysis of asymmetry indices separated SSE from the other two groups in all three parameters, while rCBF helped to distinguish between chronic focal epilepsies and single events. CONCLUSION: Preliminary results indicate that P-CT may help to identify patients with SSE during emergency workup. This technique provides important information to neurologists or emergency physicians in the difficult clinical differential diagnosis of altered mental status due to subtle status epilepticus.