Neonatal EEG seizure detection using a new signal structural complexity measure based on matching pursuit decomposition with nonstationary dictionary.

Background And Objective: In newborns, it is often difficult to accurately differentiate between seizure and non-seizure based solely on clinical manifestations. This highlights the importance of electroencephalogram (EEG) in the recognition and management of neonatal seizures. This paper proposes an effective algorithm for the detection of neonatal seizure using multichannel EEG.

Automatic fetal movement recognition from multi-channel accelerometry data.

Background And Objective: Significant health care resources are allocated to monitoring high risk pregnancies to minimize growth compromise, reduce morbidity and prevent stillbirth. Fetal movement has been recognized as an important indicator of fetal health. Studies have shown that 25% of pregnancies with decreased fetal movement in the third trimester led to poor outcomes at birth.

Identifying Emergent Mesoscopic-Macroscopic Functional Brain Network Dynamics in Infants at Term-Equivalent Age with Electric Source Neuroimaging.

To identify and characterize the functional brain networks at the time when the brain is yet to develop higher order functions in term-born and preterm infants at term-equivalent age. Although functional magnetic resonance imaging (fMRI) data have revealed the existence of spatially structured resting-state brain activity in infants, the temporal information of fMRI data limits the characterization of fast timescale brain oscillations. In this study, we use infants' high-density electroencephalography (EEG) to characterize spatiotemporal and spectral functional organizations of brain network dynamics.

EEG background features that predict outcome in term neonates with hypoxic ischaemic encephalopathy: A structured review.

Objectives: Hypoxic ischaemic encephalopathy is a significant cause of mortality and morbidity in the term infant. Electroencephalography (EEG) is a useful tool in the assessment of newborns with HIE. This systematic review of published literature identifies those background features of EEG in term neonates with HIE that best predict neurodevelopmental outcome.

Automated detection of perinatal hypoxia using time-frequency-based heart rate variability features.

Perinatal hypoxia is a cause of cerebral injury in foetuses and neonates. Detection of foetal hypoxia during labour based on the pattern recognition of heart rate signals suffers from high observer variability and low specificity. We describe a new automated hypoxia detection method using time-frequency analysis of heart rate variability (HRV) signals.