ArticleIEEE transactions on bio-medical engineering2017
Predicting Bradycardia in Preterm Infants Using Point Process Analysis of Heart Rate.
Article in IEEE transactions on bio-medical engineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 69 citations in OpenAlex.
- Feasibility of a German High-Frequency Neonatal and Pediatric Intensive Care Dataset (AIx-Neo-Guard Dataset): Secondary Data Cohort Study.JMIR pediatrics and parenting · 2026Article
- Automated hypoxia and apnea identification for neonates via enhanced respiratory signal modeling with deep learning.Scientific reports · 2025Article
- ECG-Based Biometric Recognition: A Survey of Methods and Databases.Sensors (Basel, Switzerland) · 2025Review
- Exploring Computational Techniques in Preprocessing Neonatal Physiological Signals for Detecting Adverse Outcomes: Scoping Review.Interactive journal of medical research · 2024Article
- Bradycardia May Decrease Cardiorespiratory Coupling in Preterm Infants.Entropy (Basel, Switzerland) · 2023Article
- Novel approaches to capturing and using continuous cardiorespiratory physiological data in hospitalized children.Pediatric research · 2023Review
- Edge-Enabled Heart Rate Estimation from Multisensor PPG Signals.Journal of healthcare engineering · 2023Article
- Comparison of oxygen supplementation in very preterm infants: Variations of oxygen saturation features and their application to hypoxemic episode based risk stratification.Frontiers in pediatrics · 2023Article
- On AI Approaches for Promoting Maternal and Neonatal Health in Low Resource Settings: A Review.Frontiers in public health · 2022Review
- Automated Medical Care: Bradycardia Detection and Cardiac Monitoring of Preterm Infants.Medicina (Kaunas, Lithuania) · 2021Article
- Predicting apneic events in preterm infants using cardio-respiratory and movement features.Computer methods and programs in biomedicine · 2021Article
- Early bradycardia detection and therapeutic interventions in preterm infant monitoring.Scientific reports · 2021Observational
- T-Wave Alternans in Nonpathological Preterm Infants.Annals of noninvasive electrocardiology : the official journal of the International Society for Holter and Noninvasive Electrocardiology, Inc · 2020Article
- Maturation of the Autonomic Nervous System in Premature Infants: Estimating Development Based on Heart-Rate Variability Analysis.Frontiers in physiology · 2020Article
- A Bradycardia-Based Stress Calculator for the Neonatal Intensive Care Unit: A Multisystem Approach.Frontiers in physiology · 2020Article
- Explaining Deep Classification of Time-Series Data with Learned Prototypes.CEUR workshop proceedings · 2019Article
- A Point Process Framework for the Characterization of Sleep States in Early Infancy.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2019Article
- Pre-Vent: the prematurity-related ventilatory control study.Pediatric research · 2019Observational
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
objectiveEpisodes of bradycardia are common and recur sporadically in preterm infants, posing a threat to the developing brain and other vital organs. We hypothesize that bradycardias are a result of transient temporal destabilization of the cardiac autonomic control system and that fluctuations in the heart rate signal might contain information that precedes bradycardia. We investigate infant heart rate fluctuations with a novel application of point process theory.
methodsIn ten preterm infants, we estimate instantaneous linear measures of the heart rate signal, use these measures to extract statistical features of bradycardia, and propose a simplistic framework for prediction of bradycardia.
resultsWe present the performance of a prediction algorithm using instantaneous linear measures (mean area under the curve = 0.79 ± 0.018) for over 440 bradycardia events. The algorithm achieves an average forecast time of 116 s prior to bradycardia onset (FPR = 0.15). Our analysis reveals that increased variance in the heart rate signal is a precursor of severe bradycardia. This increase in variance is associated with an increase in power from low content dynamics in the LF band (0.04-0.2 Hz) and lower multiscale entropy values prior to bradycardia.
conclusionPoint process analysis of the heartbeat time series reveals instantaneous measures that can be used to predict infant bradycardia prior to onset. SIGNIFICANCE: Our findings are relevant to risk stratification, predictive monitoring, and implementation of preventative strategies for reducing morbidity and mortality associated with bradycardia in neonatal intensive care units.
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