An SVM-based system and its performance for detection of seizures in neonates.

This work presents a multi-channel patient-independent neonatal seizure detection system based on the SVM classifier. Several post-processing steps are proposed to increase temporal precision and robustness of the system and their influence on performance is shown. The SVM-based system is evaluated on a large clinical dataset using several epoch-based and event based metrics and curves of performance are reported.

Early EEG findings in hypoxic-ischemic encephalopathy predict outcomes at 2 years.

Objective: We examined the evolution of electroencephalographic (EEG) changes after hypoxic injury.

Methods: Continuous, multichannel, video-EEG was recorded for term infants with hypoxic-ischemic encephalopathy, from <6 hours to 72 hours after delivery. One-hour segments at 6, 12, 24, and 48 hours of age of the EEG were analyzed visually, and neurologic outcome was assessed at 24 months.

Heart rate variability during sleep in healthy term newborns in the early postnatal period.

Normative time- and frequency-domain heart rate variability (HRV) measures were extracted during quiet sleep (QS) and active sleep (AS) periods in 30 healthy babies. All newborn infants studied were less than 12 h old and the sleep state was classified using multi-channel video EEG. Three bands were extracted from the heart rate (HR) spectrum: very low frequency (VLF), 0.

Interobserver agreement in neonatal seizure identification.

Objectives: Accurate diagnosis of neonatal seizures is critically important and is often made clinically, without EEG (electroencephalography) monitoring. This observational study aimed to determine the accuracy and interobserver reliability of healthcare professionals in distinguishing clinically manifested seizures from other neonatal movements, when presented with clinical histories and digital video recordings only.

Methods: Twenty digital video recordings of paroxysmal movements in term and preterm infants were selected from a video-EEG database.

EEG in the healthy term newborn within 12 hours of birth.

Objective: To characterise and quantify the EEG during sleep in healthy newborns in the early newborn period.

Methods: Continuous multi-channel video-EEG data was recorded for up to 2 hours in normal newborns within 12 hours of birth. The total amount of active (AS) and quiet sleep (QS) was calculated in the first hour of recording.

Fetal heart rate patterns in neonatal hypoxic-ischemic encephalopathy: relationship with early cerebral activity and neurodevelopmental outcome.

Despite widespread use of fetal heart rate monitoring, the timing of injury in hypoxic-ischemic encephalopathy (HIE) remains unclear. Our aim was to examine fetal heart rate patterns during labor in infants with clinical and electroencephalographic (EEG) evidence of HIE and to relate these findings to neurodevelopmental outcome. Timing of onset of pathological cardiotocographs (CTGs) was determined in each case by two blinded reviewers and related to EEG grade at birth and neurological outcome at 24 months.

Characterisation of heart rate changes and their correlation with EEG during neonatal seizures.

The effect of seizures on instantaneous HR (iHR) in 12 neonates is investigated here. HR can be readily extracted from the ECG and can be employed as an additional signal in seizure detection algorithms. The change in instantaneous HR and its correlation with the change in RMS EEG amplitude were examined.

Automated single channel seizure detection in the neonate.

Neonatal seizures are the most common neurological emergency in the neonatal period and are associated with poor long-term outcome. EEG is considered the gold standard for identification of all neonatal seizures, reducing the number of EEG electrodes required would reduce patient handling and allow faster acquisition of data. A method for automated neonatal seizure detection based on two carefully chosen cerebral scalp electrodes but trained using multi-channel EEG is presented.

Seizure detection in neonates: Improved classification through supervised adaptation.

The goal of neonatal seizure detection is the development of a patient independent system to alert staff in the neonatal intensive care unit of ongoing seizures. This study demonstrates the potential in adapting a patient independent classifier using patient specific data. Supervised adaptation is investigated using the basic gradient descent algorithm and least mean squares procedures.

Classifier models and architectures for EEG-based neonatal seizure detection.

Neonatal seizures are the most common neurological emergency in the neonatal period and are associated with a poor long-term outcome. Early detection and treatment may improve prognosis. This paper aims to develop an optimal set of parameters and a comprehensive scheme for patient-independent multi-channel EEG-based neonatal seizure detection.

Behaviour of spectral entropy, spectral edge frequency 90%, and alpha and beta power parameters during low-dose propofol infusion.

Background: In this study we analyse the behaviour, potential clinical application and optimal cortical sampling location of the spectral parameters: (i) relative alpha and beta power; (ii) spectral edge frequency 90%; and (iii) spectral entropy as monitors of moderate propofol-induced sedation.

Methods: Multi-channel EEG recorded from 12 ASA 1 (American Society of Anesthesiologists physical status 1) patients during low-dose, target effect-site controlled propofol infusion was used for this analysis. The initial target effect-site concentration was 0.

A comparison of quantitative EEG features for neonatal seizure detection.

Objective: This study was undertaken to identify the best performing quantitative EEG features for neonatal seizures detection from a test set of 21.

Methods: Each feature was evaluated on 1-min, artefact-free segments of seizure and non-seizure neonatal EEG recordings. The potential utility of each feature for neonatal seizure detection was determined using receiver operating characteristic analysis and repeated measures t-tests.

Spectral entropy as a monitor of depth of propofol induced sedation.

Objective: The aim of this prospective, observational study was to evaluate State and Response entropy (Entropy(TM) Monitor, GE Healthcare, Finland), indices as measures of moderate ("conscious") sedation in healthy adult patients receiving a low dose propofol infusion. Sedation was evaluated using: (I) the responsiveness component of the OAA/S scale (Observer's Assessment of Alertness/Sedation scale) and (II) multi-channel electroencephalogram (EEG) interpretation by a clinical expert.

Methods: 12 ASA I patients were recruited.

Gaussian process modeling of EEG for the detection of neonatal seizures.

Gaussian process (GP) probabilistic models have attractive advantages over parametric and neural network modeling approaches. They have a small number of tuneable parameters, can be trained on relatively small training sets, and provide a measure of prediction certainty. In this paper, these properties are exploited to develop two methods of highlighting the presence of neonatal seizures from electroencephalograph (EEG) signals.

Automated estimation of sedation depth from the EEG.

A method is presented for the automatic determination of a patient's level of sedation from the EEG. Six bipolar channels of EEG recorded from 12 adult patients sedated with low-dose propofol (2, 6-disopropylphenol) were used to develop a linear discriminant based system for depth of sedation monitoring using a number of quantitative EEG measures. A cross fold validation estimate of the performance of the algorithm as a patient independent system yielded a sensitivity of 74.

The effect of frequency band on quantitative EEG measures in neonates with hypoxic-ischaemic encephalopathy.

The effect of frequency ranges on three quantitative EEG measures as related to neurodevelopmental outcome at 12-24 months is reported here. Thirteen EEG records from term neonates with moderate hypoxic-ischaemic encephalopathy (HIE) were analyzed. The spectral entropy, spectral edge frequency and relative power were calculated for each EEG channel.

Multi-channel EEG based neonatal seizure detection.

A multi-channel method for patient specific and patient independent, EEG based neonatal seizure detection is presented. Two classifier configurations are proposed and tested, along with a number of classifier models. Existing methods for neonatal seizure detection have been empirical threshold based or based on a single EEG channel.

Defining the gap between electrographic seizure burden, clinical expression and staff recognition of neonatal seizures.

Background: Neonatal seizures are often subclinical, making accurate diagnosis difficult.

Objective: To describe the clinical manifestations of electrographic seizures recorded on continuous video-EEG, and to compare this description with the recognition of clinical seizures by experienced neonatal staff.

Methods: Term infants, at risk of seizures, were monitored by continuous 12-channel video-EEG from <6 hours of birth for up to 72 hours.

Electrocardiogram based neonatal seizure detection.

A method for the detection of seizures in the newborn using the electrocardiogram (ECG) signal is presented. Using a database of eight recordings, a method was developed for automatically annotating each 1-min epoch as "nonseizure" or "seizure". The system uses a linear discriminant classifier to process 41 heartbeat timing interval features.

Combination of EEG and ECG for improved automatic neonatal seizure detection.

Objective: Neonatal seizures are the most common central nervous system disorder in newborn infants. A system that could automatically detect the presence of seizures in neonates would be a significant advance facilitating timely medical intervention.

Methods: A novel method is proposed for the robust detection of neonatal seizures through the combination of simultaneously-recorded electroencephalogram (EEG) and electrocardiogram (ECG).

Treatment of neonatal seizures.

Newborn babies with unusual movements thought to represent seizures are usually given a loading dose of phenobarbitone without electroencephalography being performed. Antiepileptic drugs (AEDs) are then continued, with the outcome determined by clinical observation alone. AED treatment, often involving multiple drugs for long periods, is undesirable at a time when the brain is developing rapidly and likely to be especially vulnerable to any toxic effects.

Persistent lactic acidosis in neonatal hypoxic-ischaemic encephalopathy correlates with EEG grade and electrographic seizure burden.

Background: Predicting at birth which infants with perinatal hypoxic-ischaemic injury will progress to significant encephalopathy remains a challenge.

Objective: To determine whether lactic acidosis at birth in asphyxiated neonates could predict the grade of EEG encephalopathy by examining the relationship between time taken for the normalisation of lactate, severity of encephalopathy and seizure burden.

Methods: Continuous early video-EEG monitoring was performed in babies at risk for hypoxic-ischaemic encephalopathy.

Heart and respiration rate changes in the neonate during electroencephalographic seizure.

An investigation of changes in the neonatal electrocardiogram (ECG) and respiration signals from labelled seizure data for five neonatal patient records is reported. A decrease during seizure of 5.70% in the mean RR-interval was found.

Prediction of seizures in asphyxiated neonates: correlation with continuous video-electroencephalographic monitoring.

Background: After perinatal asphyxia, predicting which infants will develop significant hypoxic-ischemic encephalopathy and neonatal seizures remains a difficult task. High-risk markers (Apgar score, acidosis, nucleated red blood cells, and resuscitation) have been used to predict neonatal seizures with varying success. The "3 strikes" of Apgar score of <5 at 5 minutes, pH <7.

Early continuous video-EEG in acute near-total intrauterine asphyxia.

The evolution of electroencephalographic changes after acute hypoxic-ischemic injury is poorly understood, as a clear time of insult is often absent and continuous electroencephalographic monitoring in the first 3 days after such injury has not been previously reported. Infants who suffer sudden profound asphyxia, often termed "acute near-total intrauterine asphyxia", have evidence of damage to the deep gray matter. In these infants it is possible to time the onset and duration of cerebral ischemia.