On-line apnea-bradycardia detection using hidden semi-Markov models.Reportar como inadecuado

On-line apnea-bradycardia detection using hidden semi-Markov models. - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

* Corresponding author 1 LTSI - Laboratoire Traitement du Signal et de l-Image 2 GBBA - Departamento de Technologia Industrial 3 CIC-IT Rennes 4 Pôle Médico-Chirurgical de Pédiatrie et de Génétique Clinique, Néonatologie 5 LTSI - Laboratoire Traitement du Signal et de l-Image

Abstract : In this work, we propose a detection method that exploits not only the instantaneous values, but also the intrinsic dynamics of the RR series, for the detection of apnea-bradycardia episodes in preterm infants. A hidden semi-Markov model is proposed to represent and characterize the temporal evolution of observed RR series and different pre-processing methods of these series are investigated. This approach is quantitatively evaluated through synthetic and real signals, the latter being acquired in neonatal intensive care units NICU. Compared to two conventional detectors used in NICU our best detector shows an improvement of around 13% in sensitivity and 7% in specificity. Furthermore, a reduced detection delay of approximately 3 seconds is obtained with respect to conventional detectors.

Keywords : Biological system modeling Electrocardiography Feature extraction Hidden Markov Models Quantization medical signal processing paediatrics NICU RR series intrinsic dynamics detection method Hidden Semi-Markov Models neonatal intensive care units online apnea-bradycardia detection preterm infants

Autor: Miguel Altuve - Guy Carrault - Alain Beuchee - Patrick Pladys - Alfredo Hernandez -

Fuente: https://hal.archives-ouvertes.fr/


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