A self-adapting system for the automated detection of inter-ictal epileptiform discharges.

ABSTRACT:

Purpose

Scalp EEG remains the standard clinical procedure for the diagnosis of epilepsy. Manual detection of inter-ictal epileptiform discharges (IEDs) is slow and cumbersome, and few automated methods are used to assist in practice. This is mostly due to low sensitivities, high false positive rates, or a lack of trust in the automated method. In this study we aim to find a solution that will make computer assisted detection more efficient than conventional methods, while preserving the detection certainty of a manual search.

Methods

Our solution consists of two phases. First, a detection phase finds all events similar to epileptiform activity by using a large database of template waveforms. Individual template detections are combined to form "IED nominations", each with a c

SUBMITTER: Lodder SS 

PROVIDER: S-EPMC3893182 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature