S156 Abstracts of Poster Presentations / Clinical Neurophysiology 125, Supplement 1 (2014) S1–S339

are presented for review. Confirmed events are stored and marked asdetected IEDs.Results: Evaluation was performed on a test set of 15 EEGs (306 min, 244IEDs marked by an experienced reviewer). A total of 8426 events werenominated as epileptiform events, and 241 of the 244 IEDs were detected(25.8 fp/min over all certainty levels). Using the described method, 15iterations (10 events reviewed per iteration) were performed on each EEG,and the number of confirmed IEDs was counted after each iteration. Resultsshow that 74% of all marked IEDs were found after five iterations, 90% afterten iterations, and 95% after fifteen iterations. The review time for eachiteration was on average twenty seconds, resulting in a total review time offive minutes per EEG.Conclusions: The use of automated IED detection algorithms are limitedby their high number of false detections. The proposed method shows howautomated detection can be used to find IEDs in a fast and efficient man-ner, regardless of a high false detection rates. Compared to conventionalmethods, it can improve review times significantly and make long-termrecordings for epilepsy diagnosis more feasible.

P399EEG independent component analysis and 3D localization of brainpathological areas

A. IvanovNeurosoft Ltd., Software, Ivanovo, Russian Federation

Independent Component Analysis (ICA) is a computational method widelyused in practice for EEG artifact removal. ICA can be also used for theimproving of 3D dipole localization method. ICA decomposition of an EEGallows to separate independent components containing paroxysmal activity.Independent components without paroxysmal activity are to be excludedfrom analysis. The target trace processed with ICA contains only fragmentswith paroxysmal activity. This technique provides clear visualization ofparoxysmal events on trace and improves results of 3D dipole localization.The validity and performance of the approach were confirmed by medicaltrial. A total of 8 patients aged from 13 to 58 year with clinically provenepilepsy were examined. Long-term EEG was recorded from all the patients.Recorded EEG traces were processed using ICA method. Raw EEG tracesand traces obtained after ICA processing were exposed to 3D localizationby dipole model using BrainLoc 6.0 software for 3D dipole localization(Neurosoft, Russia).Research shows that the graphic representation of paroxysmal events ontrace is denser for ICA-processed EEG trace than for raw trace. So, the 3Ddipole localization of ICA-processed EEG traces is far more efficient than 3Dlocalization of raw EEG traces.Conclusion: This composite method helps to reduce redundant data forbetter feature extraction. The efficacy of the combined algorithm wasproven during medical trial.

P400Home Video Telemetry vs Inpatient Telemetry – an evaluativecomparison

S. Biswas, R. Luz, F. BrunnhuberKing’s College Hospital NHS Trust, Clinical Neurophysiology, London, UnitedKingdom

Objective: Evaluation of current attended Home VT practice, looking atvideo quality.Is video quality in Home Video Telemetry worse than Inpatient Telemetry?Method: One of the first studies completed to assess our Home VideoTelemetry (HVT) practice, which commenced in 2012, was to retrospec-tively compare the video quality against Inpatient Video Recording, consid-ering the latter as the gold standard. A pilot study was conducted in 2008using the Test-Re-Test design on 5 paediatric patients.Patients (n=28) referred for diagnostic or presurgical evaluation wereincluded in each group over a period of one year.Data were collected from referral spreadsheets, King’s ePR and telemetryarchive.Consensus scoring, by 2 scorers were carried out of the events only. Clustersof events were considered as one event.Variables compared included - visibility of body part of interest; visibilityof eyes; time of event; lighting; contrast; sound quality; quality of picturewhen amplified to 200%

Data were quantified and statistical evaluation carried out using Shapiro-Wilk and Chi-square tests. P-value of ≤0.05 was considered statisticallysignificant.Results:• Significant differences were demonstrated in - Lighting and Contrastbetween the two groups (Home VT performed better in both).

• Quality of Picture When Amplified was slightly better on the HVT group.Conclusion: HVT is not inferior to IPT; in fact it surpasses IPT in certainaspects like lighting and contrast. Results reconfirmed in a larger sample ofpatients with more variables.

P401A new approach for analysis of gamma event-related oscillatoryresponses in Alzheimer’s disease

G. Yener1,2,3,4, D.D. Emek-Savas1, B. Guentekin1, E. Basar11Istanbul Kultur University, Brain Dynamics, Cognition and Complex SystemsResearch Center, Istanbul, Turkey; 2Dokuz Eylul University, Brain DynamicsMultidisciplinary Research Center, Izmir, Turkey; 3Dokuz Eylul University,Department of Neurosciences, Izmir, Turkey; 4Dokuz Eylul University MedicalSchool, Department of Neurology, Izmir, Turkey

Background: The changes in brain dynamics of Alzheimer’s disease (AD)can be detected by brain event-related oscillations (ERO). Gamma oscil-latory responses were explored in many neuropsychiatric conditions andreported to be related to cognition.Methods: In this preliminary study, we explored ERO target gamma re-sponses of AD subjects (n=12) and healthy elderly controls (HC) (n=13)in four time frames of post-stimulus 0-200, 200-400, 400-600, 600-800ms and a wide window of 0-800 ms. We calculated event-related spectralpower (ERSP) in two frequency bands (28-39 Hz and 40-48 Hz). Repeatedmeasures of ANOVA was performed for 4× anteriorposterior, 3× coronal,2× frequency bands.Results: The group difference of gamma ERO responses was not evident,however there was a significant frequency × coronal × group effect(p<0.002) in 0-200 ms time window, showing lower amplitudes at 28-39Hz over right sided electrodes in AD. In 600-800 ms time interval, anterior-posterior x group effect was significant (p<0.044), indicating late responsesover frontal regions in AD. These significant findings disappeared whenanalysis was done in 0-800 msec time block. Analyses in time intervals of200-400 ms and 400-600 ms did not show any significant group effect.

Figure 1