Evaluation of On-Line Bradycardia Boundary Detectors from Neonatal Clinical Data
Résumé
this paper aims at investigating different methods for the detection of the start and end of bradycardias in heart rate signal of premature babies. We present two methods based on a disturbance detector and on a decision tree that are compared to classical thresholding approaches. Decision tree obtained the best detection results (Se=78.2%, PP=68.7%) against the disturbance detector (Se=90.2%, PP=61.3%) and the best thresholding method (Se=92.5%, PP=46.5%). Moreover, the decision tree exhibits better performance for the boundaries estimation (median delay = 7-5 seconds) than the disturbance detector (median delay = 8-5 seconds) with a better stability (STD=8.5 to 8.7s vs. STD=35.3 to 19.9s). These methods will be integrated to the BabyTalk project which aims at summarizing neonatal clinical data as text in order to improve data management in Neonatal ICU.
Domaines
Intelligence artificielle [cs.AI]
Origine : Fichiers produits par l'(les) auteur(s)
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