Implementation of Lagged Phase Space for Spike Detection

The presurgical evaluation patients for resective epilepsy surgery require localization of the epileptogenic cortical zone (EZ). The detection and analysis of interictal and ictal epileptiform spikes is of major importance for identifying this area. The “irritative zone” of cortex with interictal spikes are usually revealed intraoperatively during acute electrocorticogram (ECoG). Since ECoG recordings cannot be completely visually reviewed in a reasonable amount of time, computer algorithms for automatic detection of seizures and spikes were developed. In this article we present a method of spike detection in ECoG signal using lagged phase space (LPS). Vectors in lagged phased space are treated as features. For spike detection we used expectation-maximization (EM) clustering algorithm. In this way we obtained quite high detection accuracy 96.4%.