Multivariate ECG analysis for apnoea?bradycardia detection and characterisation in preterm infants. - Université de Rennes Accéder directement au contenu
Article Dans Une Revue International Journal of Biomedical Engineering and Technology (IJBET) Année : 2011

Multivariate ECG analysis for apnoea?bradycardia detection and characterisation in preterm infants.

Résumé

An analysis of the information content of new features derived from the electrocardiogram of preterm infants is presented. Beat detection and segmentation methods, specifically adapted to this population through evolutionary algorithms, led to an improved sensitivity and positive predictive value. RR interval, R-wave amplitude and QRS duration time-series were extracted at rest (T1), before (T2), during (T3) and after (T4) apnoea-bradycardia episodes. Significant variations for T1-T2 vs. T1-T3 and T1-T3 vs. T1-T4 were observed. Results reveal changes in the R-wave amplitude and QRS duration at the onset and termination of apnoea-bradycardia episodes which could be useful for their detection and characterisation.
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Dates et versions

hal-00906294 , version 1 (19-11-2013)

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Citer

Miguel Altuve, Guy Carrault, Julio Cruz, Alain Beuchée, Patrick Pladys, et al.. Multivariate ECG analysis for apnoea?bradycardia detection and characterisation in preterm infants.. International Journal of Biomedical Engineering and Technology (IJBET), 2011, 5 (2-3), pp.247-265. ⟨10.1504/IJBET.2011.039201⟩. ⟨hal-00906294⟩
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