USING AUTOMATED ALGORITHMS TO ANALYZECIRCADIAN CHANGES OF EEG BIOMARKERSPROPERTIES IN PATIENTS WITH EPILEPSY

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F16%3A00305032" target="_blank" >RIV/68407700:21230/16:00305032 - isvavai.cz</a>

Výsledek na webu

<a href="http://onlinelibrary.wiley.com/doi/10.1111/epi.13609/epdf" target="_blank" >http://onlinelibrary.wiley.com/doi/10.1111/epi.13609/epdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/epi.13609" target="_blank" >10.1111/epi.13609</a>

Jazyk výsledku

angličtina

Název v původním jazyce

USING AUTOMATED ALGORITHMS TO ANALYZECIRCADIAN CHANGES OF EEG BIOMARKERSPROPERTIES IN PATIENTS WITH EPILEPSY

Popis výsledku v původním jazyce

Purpose: Visual assessment of EEG biomarkers dynamics is highly timeconsuming and very subjective. We developed algorithms for high fre-quency oscillations and interictal discharges (spike) detection. With thesemethods we can process large amount of data in reasonable time and withobjective results. With this methods the long term analysis can bring fewmore information for the more precise epilepsy diagnosis and surgery.Method: Both algorithms were used on set of 6 patients invasive EEGrecordings. Recordings have length of 17.9  5.7 h and were recordedwith 114  22 channels. Results of quantitative analysis were processedin respect to sleep/wake cycle. We compare output of automated detec-tion algorithms with results of studies where were biomarkers labelledvisually.Results: The trends in detected biomarkers from the automated algo-rithms follow circadian dynamics. In respect to the sleep/wake cyclephases occurrence of the high frequency oscillations is significantly morefrequent in non-REM sleep phase as it was presented in previous studies.Conclusion: The automatic detection shows ability to monitor trends inthe occurrence of EEG biomarkers during circadian rhythms. When weexperimentally use detectors to several days long recordings wererevealed ultradian changes in trends detected by automated methods. Ournext aim will be analysis of circadian and ultradian changes on dataset ofpatients with focal cortical dysplasia. We try to distinguish type I and IIon behalf of these changes and biomarkers parameters.

Název v anglickém jazyce

USING AUTOMATED ALGORITHMS TO ANALYZECIRCADIAN CHANGES OF EEG BIOMARKERSPROPERTIES IN PATIENTS WITH EPILEPSY

Popis výsledku anglicky

Purpose: Visual assessment of EEG biomarkers dynamics is highly timeconsuming and very subjective. We developed algorithms for high fre-quency oscillations and interictal discharges (spike) detection. With thesemethods we can process large amount of data in reasonable time and withobjective results. With this methods the long term analysis can bring fewmore information for the more precise epilepsy diagnosis and surgery.Method: Both algorithms were used on set of 6 patients invasive EEGrecordings. Recordings have length of 17.9  5.7 h and were recordedwith 114  22 channels. Results of quantitative analysis were processedin respect to sleep/wake cycle. We compare output of automated detec-tion algorithms with results of studies where were biomarkers labelledvisually.Results: The trends in detected biomarkers from the automated algo-rithms follow circadian dynamics. In respect to the sleep/wake cyclephases occurrence of the high frequency oscillations is significantly morefrequent in non-REM sleep phase as it was presented in previous studies.Conclusion: The automatic detection shows ability to monitor trends inthe occurrence of EEG biomarkers during circadian rhythms. When weexperimentally use detectors to several days long recordings wererevealed ultradian changes in trends detected by automated methods. Ournext aim will be analysis of circadian and ultradian changes on dataset ofpatients with focal cortical dysplasia. We try to distinguish type I and IIon behalf of these changes and biomarkers parameters.

Druh

O - Ostatní výsledky

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů