Automatic detection of prominent interictal spikes in intracranial EEG: validation of an algorithm and relationsip to the seizure onset zone.

ABSTRACT:

Objective

To develop an algorithm for the automatic quantitative description and detection of spikes in the intracranial EEG and quantify the relationship between prominent spikes and the seizure onset zone.

Methods

An algorithm was developed for the quantification of time-frequency properties of spikes (upslope, instantaneous energy, downslope) and their statistical representation in a univariate generalized extreme value distribution. Its performance was evaluated in comparison to expert detection of spikes in intracranial EEG recordings from 10 patients. It was subsequently used in 18 patients to detect prominent spikes and quantify their spatial relationship to the seizure onset area.

Results

The algorithm displayed an average sensitivity of 63.4% with a false det

SUBMITTER: Gaspard N 

PROVIDER: S-EPMC5123744 | biostudies-literature | 2014 Jun

REPOSITORIES: biostudies-literature