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UID:402@cran.univ-lorraine.fr
DTSTART;TZID=Europe/Paris:20240415T150000
DTEND;TZID=Europe/Paris:20240415T160000
DTSTAMP:20240414T175218Z
URL:https://www.cran.univ-lorraine.fr/events/seminaire-vicente-zarzoso/
SUMMARY:Séminaire Vicente Zarzoso
DESCRIPTION:Speaker: Vicente Zarzoso (Université Côte d’Azur\, Nice)\nW
 ebsite: https:/webusers.i3s.unice.fr/~zarzoso/\nTitle: Tensor decompositio
 n of ECG records for persistent atrial fibrillation analysis\n\nConsidered
  as the last great frontier of cardiac electrophysiology\, atrial fibrilla
 tion (AF) is the most common sustained arrhythmia encountered in clinical 
 practice\, responsible for high hospitalization rates and a significant pr
 oportion of brain strokes in the Western world. Analyzing AF electrophysio
 logical complexity noninvasively requires the extraction of the atrial act
 ivity (AA) signal from the electrocardiogram (ECG). To perform this task\,
  most approaches including classical average beat subtraction need suffici
 ently long ECG records\, thus limiting real-time analysis. Matrix factoriz
 ations can also be used for AA signal estimation by exploiting the spatial
  diversity of the multi-lead ECG\, but require some constraints to guarant
 ee uniqueness that may lack physiological grounds and hinder results inter
 pretation.\n\nThis talk will review recent results obtained at the I3S Lab
 oratory\, UMR 7271\, Université Côte d'Azur\, CNRS\, on tensor decomposi
 tions for noninvasive AA signal extraction in AF ECGs\, which guarantee un
 iqueness under milder constraints on their factors. Specifically\, the blo
 ck term decomposition (BTD) has been shown to be particularly suitable to 
 address this biomedical problem\, as atrial and ventricular cardiac activi
 ty sources can be modeled by matrices with special structure. The structur
 e of these matrices ensures model uniqueness while their rank is linked to
  signal complexity. In this framework\, we have put forward the Hankel and
  Löwner BTD as AA extraction tools in AF ECG episodes\, with validation i
 n a population of persistent AF patients and several challenging types of 
 ECG segments\, including short beat-to-beat intervals and low-amplitude fi
 brillatory waves. Accurate AA extraction can be achieved from ECG segments
  as short as a single heartbeat. We have also developed a robust computati
 onal algorithm - the so-called alternating group lasso BTD (BTD-AGL) - to 
 simultaneously recover the model structure (number of block terms and mult
 ilinear rank of each term) and the model factors. In addition\, tensor mod
 eling allows us to derive a novel index to quantify AF complexity nonivasi
 vely\, useful to characterize stepwise catheter ablation\, a first-line th
 erapeutic option for the treatment of persistent forms of the arrhythmia. 
 The index correlates with the expected decrease in AF complexity over abla
 tion steps and is predictive of AF recurrence\, which presents clear clini
 cal interest.\n\nTeams: https://teams.microsoft.com/l/meetup-join/19%3aaa7
 9c15ac331466aa8ad98cbecb29ab2%40thread.tacv2/1713113334265?context=%7b%22T
 id%22%3a%22158716cf-46b9-48ca-8c49-c7bb67e575f3%22%2c%22Oid%22%3a%22c4a8ae
 a2-7ce5-4ee9-b6c5-9fee62ad0257%22%7d\n\nSiMuL web site: https:/cran-simul.
 github.io/seminars
CATEGORIES:Département BioSiS,Séminaires projet SiMul
LOCATION:CRAN - FST - 4ème\, Campus Sciences\, Boulevard des Aiguillettes\
 , Vandoeuvre-lès-Nancy\, 54506\, France
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=Campus Sciences\, Boulevard
  des Aiguillettes\, Vandoeuvre-lès-Nancy\, 54506\, France;X-APPLE-RADIUS=
 100;X-TITLE=CRAN - FST - 4ème:geo:0,0
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