Paper published in a book (Scientific congresses and symposiums)
A Graph Signal Processing Approach to Study High Density EEG Signals in Patients with Disorders of Consciousness
Mortaheb, Sepehr; Annen, Jitka; Chatelle, Camille et al.
2019In A Graph Signal Processing Approach to Study High Density EEG Signals in Patients with Disorders of Consciousness
Peer reviewed
 

Files


Full Text
gsp_doc.pdf
Publisher postprint (1.03 MB)
Download

All documents in ORBi are protected by a user license.

Send to



Details



Abstract :
[en] Graph signal processing (GSP) is a novel approach to analyse multi-dimensional neuroimaging data, constraining functional measures by structural characteristics in a single framework (i.e. graph signals). In this approach, functional time series are assigned to the vertices of the underlying weighted graph and GSP analysis is performed in each time point of the signal. Here we used GSP to study local brain connectivity changes in patients with disorders of consciousness based on resting state high density electroencephalography (hdEEG) recordings. Total variation of the graph signals is a measure of signal smoothness over the underlying graph. In this study, we constructed the underlying graph based on the geometrical distances between each electrode pairs in such a way that local smoothness of the signal can be studied. Total variation analysis in α-band showed that in the pathological states of altered consciousness, local short range communication of brain regions in this frequency band is stronger than in healthy states which shows that information is segregated in local regions in patients with disorders of consciousness. © 2019 IEEE.
Disciplines :
Computer science
Author, co-author :
Mortaheb, Sepehr  ;  Université de Liège - ULiège > Consciousness-Physiology of Cognition
Annen, Jitka  ;  Université de Liège - ULiège > Consciousness-Coma Science Group
Chatelle, Camille ;  Université de Liège - ULiège > Consciousness-Coma Science Group
Cassol, Helena ;  Université de Liège - ULiège > GIGA
Martens, Géraldine  ;  Université de Liège - ULiège > Consciousness-Coma Science Group
Thibaut, Aurore ;  Université de Liège - ULiège > Consciousness-Coma Science Group
Gosseries, Olivia  ;  Université de Liège - ULiège > Consciousness-Coma Science Group
Laureys, Steven  ;  Université de Liège - ULiège > Consciousness-Coma Science Group
Language :
English
Title :
A Graph Signal Processing Approach to Study High Density EEG Signals in Patients with Disorders of Consciousness
Publication date :
2019
Event name :
41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019
Event date :
23 July 2019 through 27 July 2019
Audience :
International
Main work title :
A Graph Signal Processing Approach to Study High Density EEG Signals in Patients with Disorders of Consciousness
Publisher :
IEEE
Peer reviewed :
Peer reviewed
Commentary :
152547 9781538613115
Available on ORBi :
since 11 March 2020

Statistics


Number of views
134 (12 by ULiège)
Number of downloads
418 (13 by ULiège)

Scopus citations®
 
14
Scopus citations®
without self-citations
14
OpenCitations
 
4

Bibliography


Similar publications



Contact ORBi