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DOI: 10.1145/2093698.2093811

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ISABEL'11: 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, Barcelona : Europe (2011)

Automated localisation and classification of abnormal beats in electrocardiograms using parsimonious wavelet analysis

Ahmad Khoureich Ka 1, Dimitri Petritis (  Corresponding author ) 1

(2011)

We report on a work in progress aiming at automatically analysing electrocardiograms with the help of wavelet bases. The objective we have fixed was to introduce a parsimonious and computationally efficient method --- that can be ultimately incorporated on standard ECG recording devices --- to automatically localise points of interest and decide whether they are normal or not and, for abnormal points, assign them a given class of abnormality. The task we have already achieved is the localisation and identification of normal QRS complexes. Identification and localisation of other features, like premature atrial or ventricular beats, fibrillation, noise, bundle branch block beats, ectopic beats, etc. is in progress but the so far obtained preliminary results are very encouraging.

1:	Institut de Recherche Mathématique de Rennes (IRMAR)
	CNRS : UMR6625 – Université de Rennes 1 – École normale supérieure de Cachan - ENS Cachan – Institut National des Sciences Appliquées (INSA) : - RENNES – Université de Rennes II - Haute Bretagne

Research team: Théorie ergodique

Subject

:

Life Sciences/Human health and pathology/Cardiology and cardiovascular system Mathematics/Probability Mathematics/Statistics Statistics/Statistics Theory

Keyword(s): Discrete wavelet basis decomposition – Electrocardiogram

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From: Dimitri Petritis <>

Submitted on: Wednesday, 14 March 2012 18:50:38

Updated on: Wednesday, 14 March 2012 18:50:38