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

International audienceIn 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

A model-based approach for the evaluation of vagal and sympathetic activities in a newborn lamb.

International audienceThis paper proposes a baroreflex model and a recursive identification method to estimate the time-varying vagal and sympathetic contributions to heart rate variability during autonomic maneuvers. The baroreflex model includes baroreceptors, cardiovascular control center, parasympathetic and sympathetic pathways. The gains of the global afferent sympathetic and vagal pathways are identified recursively. The method has been validated on data from newborn lambs, which have been acquired during the application of an autonomic maneuver, without medication and under beta-blockers. Results show a close match between experimental and simulated signals under both conditions. The vagal and sympathetic contributions have been simulated and, as expected, it is possible to observe different baroreflex responses under beta-blockers compared to baseline conditions

Apports nutritionnels précoces et croissance postnatale chez l'enfant prématuré né avant 32 semaines d'aménorrhée

RENNES1-BU Santé (352382103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Effet de la maturation sur la fiabilité des mesures de diffusion du faisceau cortico-spinal chez l'ancien prématuré

RENNES1-BU Santé (352382103) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Early-onset neonatal sepsis is associated with a high heart rate during automatically selected stationary periods

International audienceAIM: This study examined the heart rate variability characteristics associated with early-onset neonatal sepsis in a prospective, observational controlled study.METHODS: Eligible patients were full-term neonates hospitalised with clinical signs that suggested early-onset sepsis and a C-reactive protein of >10 mg/L. Sepsis was considered proven in cases of symptomatic septicaemia, meningitis, pneumonia or enterocolitis. Heart rate variability parameters (n = 16) were assessed from five-, 15- and 30-minute stationary sequences automatically selected from electrocardiographic recordings performed at admission and compared with a control group using the U-test with post hoc Benjamini-Yekutieli correction. Stationary sequences corresponded to the periods with the lowest changes of heart rate variability over time.RESULTS: A total of 40 full-term infants were enrolled, including 14 with proven sepsis. The mean duration of the cardiac cycle length was lower in the proven sepsis group than in the control group (n = 11), without other significant changes in heart rate variability parameters. These durations, measured in five-minute stationary periods, were 406 (367-433) ms in proven sepsis group versus 507 (463-522) ms in the control group (p < 0.05).CONCLUSION: Early-onset neonatal sepsis was associated with a high mean heart rate measured during automatically selected stationary periods

Detection of Apnea Bradycardia from ECG Signals of Preterm Infants Using Layered Hidden Markov Model

International audienceApnea-bradycardia (AB) is a common complication in prematurely born infants, which is associated with reduced survival and neurodevelopmental outcomes. Thus, early detection or predication of AB episodes is critical for initiating preventive interventions. To develop automatic real-time operating systems for early detection of AB, recent advances in signal processing can be employed. Hidden Markov Models (HMM) are probabilistic models with the ability of learning different dynamics of the real time-series such as clinical recordings. In this study, a hierarchy of HMMs named as layered HMM was presented to detect AB episodes from pre-processed single-channel Electrocardiography (ECG). For training the hierarchical structure, RR interval, and width of QRS complex were extracted from ECG as observations. The recordings of 32 premature infants with median 31.2 (29.7, 31.9) weeks of gestation were used for this study. The performance of the proposed layered HMM was evaluated in detecting AB. The best average accuracy of 97.14 +/- 0.31% with detection delay of - 5.05 +/- 0.41 s was achieved. The results show that layered structure can improve the performance of the detection system in early detecting of AB episodes. Such system can be incorporated for more robust long-term monitoring of preterm infants

Coupled Hidden Markov Model-Based Method for Apnea Bradycardia Detection.

International audienceIn this paper, we present a novel framework for the coupled hidden Markov model (CHMM), based on the forward and backward recursions and conditional probabilities, given a multidimensional observation. In the proposed framework, the interdependencies of states networks are modeled with Markovian-like transition laws that influence the evolution of hidden states in all channels. Moreover, an offline inference approach by maximum likelihood estimation is proposed for the learning procedure of model parameters. To evaluate its performance, we first apply the CHMM model to classify and detect disturbances using synthetic data generated by the FitzHugh-Nagumo model. The average sensitivity and specificity of the classification are above 93.98% and 95.38% and those of the detection reach 94.49% and 99.34%, respectively. The method is also evaluated using a clinical database composed of annotated physiological signal recordings of neonates suffering from apnea-bradycardia. Different combinations of beat-to-beat features extracted from electrocardiographic signals constitute the multidimensional observations for which the proposed CHMM model is applied, to detect each apnea bradycardia episode. The proposed approach is finally compared to other previously proposed HMM-based detection methods. Our CHMM provides the best performance on this clinical database, presenting an average sensitivity of 95.74% and specificity of 91.88% while it reduces the detection delay by -0.59 s

Early arterial pressure monitoring and term-equivalent age MRI findings in very preterm infants

International audienceIntroduction Variability of arterial blood pressure (ABP) has been associated with intraventricular hemorrhage in very preterm neonates (VPT) and may predict other brain lesions assessed at term-equivalent of age (TEA). Methods This was a prospective single-center study including VPT with early invasive continuous ABP monitoring and assessed at TEA using brain magnetic resonance imaging (TEA-MRI). The association between early mean ABP (MABP) and TEA-MRI findings was modeled by multivariate logistic regression analysis using covariates selected by the LASSO method. Results Among 99 VPT, the LASSO procedure selected consecutive periods of lowest MABP of 30 min on day 1 (d1) and 10 min on day 2 (d2) as the most relevant durations to predict TEA-MRI findings (OR [95% CI], 1.11 [1.02-1.23], p = 0.03 and 1.13 [1.01-1.27], p = 0.03, respectively). ROC curve analysis showed optimal thresholds at 30.25 mmHg on d1 and 33.25 mmHg on d2. This significant association persisted after adjustment with covariates including birthweight, gestational age, sex, and inotrope exposure. Final models selected by LASSO included the decile of the birthweight and lowest MABP for 30 min on d1 and 10 min on d2, for which the areas under the ROC curve were 74% and 75%, respectively. Conclusion Early continuous ABP monitoring may predict brain TEA-MRI findings in VPT. Impact Early arterial blood pressure monitoring may contribute to predicting brain damage upon MRI at term-equivalent of age for infants born very preterm. Careful blood pressure continuous monitoring in very preterm infants may identify infants at risk of long-term brain damage. Umbilical artery catheterization provides the best option for continuously monitoring arterial blood pressure in very preterm infants

A novel, short and easy-to-perform method to evaluate newborns’ social olfactory preferences

International audienceHumans’ early olfactory perception has been studied mainly within the framework of mother–offspring interactions and only a few studies have focused on newborns’ abilities to discriminate body odors per se. The aim of this study was to develop a method to evaluate olfactory social preferences of infants at term-equivalent age. Twenty dyads of infants (10 born preterm and 10 born at term) at term-equivalent age and their mothers were included. We analyzed the behavioral reactions of infants to their mother's upper-chest odor (that bears social, non-food related information). The two impregnated gauzes and a control gauze were presented to the infants for 10 s each, in a random order. We compared two durations of gauze impregnation: 30 min and 12 h. This study reveals that mothers’ upper chest emits sufficient olfactory information to induce reactions in infants born full-term or born preterm and that a short impregnation is preferable to evaluate their perception of body odors, notably for those born preterm