Article ID Journal Published Year Pages File Type
6008765 Clinical Neurophysiology 2012 7 Pages PDF
Abstract

ObjectiveTo investigate the accuracy of human listeners in identifying epileptic seizures and seizure lateralisation from audified EEG signals.MethodsEEG data from 17 temporal lobe epilepsy patients (9 male, 8 female; aged 23-55) was converted to audio format by 60× time compression. Using a subset of 19% of the data, five auditory participants (2 female, 3 male; aged 23-58) were trained to identify seizures and their lateralisation by listening to audified EEG signals from difference electrodes P3-T5 and P4-T6. Following training, seizure detection performance of the auditory participants was tested using the remaining data.ResultsAllowing a 5 s auditory time margin for successful detection, the mean sensitivity of the five auditory participants was 89.6% (SD 8.3%) with a false detection rate of only 0.0068/h (SD 0.0077/h). The mean accuracy of seizure lateralisation identification was 77.6% (SD 7.1%).ConclusionsWith a limited amount of training, humans can detect seizures and seizure lateralisation from audified EEG signals of electrodes P3-T5 and P4-T6 with accuracy comparable to visual assessment of full EEG traces (21 electrodes) by an expert encephalographer.SignificanceA more efficient and accurate clinical tool for assessing EEG data based on audification may be developed, which will improve diagnosis and treatment of epilepsy.

► Outlines a simple method for audification of EEG signals for the purpose of seizure detection and seizure focus lateralisation. ► With only 2 h of training, non expert subjects can detect seizures from audified EEG signals of 2 difference electrodes with a comparable degree of accuracy as can be done visually from review of EEG traces using the 10-20 electrode placement by an expert electroencephalographer. ► Using this method, predictions of seizure lateralisation are more accurate for the seizures which are easiest to detect.

Related Topics
Life Sciences Neuroscience Neurology
Authors
, , , ,