Automated detection of epileptic ripples in MEG using beamformer-based virtual sensors.


Por: Migliorelli C, Alonso-Lopez JF, Romero-Lafuente S, Nowak R, Russi A and Mañanas MA

Publicada: 1 ago 2017
Resumen:
In epilepsy, high-frequency oscillations (HFOs) are expressively linked to the seizure onset zone (SOZ). The detection of HFOs in the noninvasive signals from scalp electroencephalography (EEG) and magnetoencephalography (MEG) is still a challenging task. The aim of this study was to automate the detection of ripples in MEG signals by reducing the high-frequency noise using beamformer-based virtual sensors (VSs) and applying an automatic procedure for exploring the time-frequency content of the detected events.

Filiaciones:
Migliorelli C:
 Department of Automatic Control (ESAII), Biomedical Engineering Research Center (CREB), Universitat Politènica de Catalunya (UPC), Barcelona, Spain. Biomedical Research Networking center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
ISSN: 17412560





Journal of Neural Engineering
Editorial
IOP Publishing Ltd, No.2 The Distillery, Glassfields, Avon Street, Bristol BS2 0GR, ENGLAND, Reino Unido
Tipo de documento: Article
Volumen: 14 Número: 4
Páginas: 46013-46013
WOS Id: 000405590200003
ID de PubMed: 28327467
imagen Open Access

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