Automatic detection of high-frequency oscillations in invasive recordings

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00064203%3A_____%2F13%3A10389811" target="_blank" >RIV/00064203:_____/13:10389811 - isvavai.cz</a>

Alternative codes found

RIV/68407700:21230/13:00205882 RIV/00216208:11130/13:10389811

Result on the web

<a href="https://doi.org/10.1109/MeMeA.2013.6549741" target="_blank" >https://doi.org/10.1109/MeMeA.2013.6549741</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/MeMeA.2013.6549741" target="_blank" >10.1109/MeMeA.2013.6549741</a>

Result language

angličtina

Original language name

Automatic detection of high-frequency oscillations in invasive recordings

Original language description

High-frequency oscillations (HFOs) represent relatively new electrographic marker of epileptogenic tissue. It is starting to be used in presurgical examination to better plan surgical resection and to improve outcome of epilepsy surgery. Development of new techniques of unsupervised HFOs detection is required to further investigate the role of HFO in the pathophysiology of epilepsy and to increase the yield of presurgical examination. In this study we applied an envelope distribution modelling technique on experimental and human invasive data to detect HFOs. Application to experimental microelectrode recordings demonstrated satisfactory results with sensitivity 89.9% and false positive rate 2.1 per minute. Application of this algorithm to human invasive recordings achieved sensitivity 80%. High numbers of false positive detections required utilization of post-processing steps to eliminate the majority of them. This study shows that envelope distribution modelling represents a promising approach to detect HFOs in intracranial recordings. Advantages of this approach are quick adjustments to changes in background activity and resistance to signal non-stationarities. However, successful application to clinical practice requires development of secondary processing steps that will decrease the rate of false positive detections.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

30103 - Neurosciences (including psychophysiology)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2013

Confidentiality

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

Article name in the collection

MeMeA 2013 - IEEE International Symposium on Medical Measurements and Applications, Proceedings

ISBN

978-1-4673-5196-6

ISSN

—

e-ISSN

neuvedeno

Number of pages

5

Pages from-to

228-232

Publisher name

IEEE

Place of publication

New York

Event location

Gatineau, QC

Event date

Mar 4, 2013

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000326748000048