Overcoming the practical challenges of electroencephalography for very preterm infants in the neonatal intensive care unit

Generalized Camera-Based Infant Sleep-Wake Monitoring in NICUs: A Multi-Center Clinical Trial

The infant sleep-wake behavior is an essential indicator of physiological and neurological system maturity, the circadian transition of which is important for evaluating the recovery of preterm infants from inadequate physiological function and cognitive disorders. Recently, camera-based infant sleep-wake monitoring has been investigated, but the challenges of generalization caused by variance in infants and clinical environments are not addressed for this application. In this paper, we conducted a multi-center clinical trial at four hospitals to improve the generalization of camera-based infant sleep-wake monitoring. Using the face videos of 64 term and 39 preterm infants recorded in NICUs, we proposed a novel sleep-wake classification strategy, called consistent deep representation constraint (CDRC), that forces the convolutional neural network (CNN) to make consistent predictions for the samples from different conditions but with the same label, to address the variances caused by infants and environments. The clinical validation shows that by using CDRC, all CNN backbones obtain over 85% accuracy, sensitivity, and specificity in both the cross-age and cross-environment experiments, improving the ones without CDRC by almost 15% in all metrics. This demonstrates that by improving the consistency of the deep representation of samples with the same state, we can significantly improve the generalization of infant sleep-wake classification.

Multimodality Video Acquisition System for the Assessment of Vital Distress in Children

In children, vital distress events, particularly respiratory, go unrecognized. To develop a standard model for automated assessment of vital distress in children, we aimed to construct a prospective high-quality video database for critically ill children in a pediatric intensive care unit (PICU) setting. The videos were acquired automatically through a secure web application with an application programming interface (API). The purpose of this article is to describe the data acquisition process from each PICU room to the research electronic database. Using an Azure Kinect DK and a Flir Lepton 3.5 LWIR attached to a Jetson Xavier NX board and the network architecture of our PICU, we have implemented an ongoing high-fidelity prospectively collected video database for research, monitoring, and diagnostic purposes. This infrastructure offers the opportunity to develop algorithms (including computational models) to quantify vital distress in order to evaluate vital distress events. More than 290 RGB, thermographic, and point cloud videos of each 30 s have been recorded in the database. Each recording is linked to the patient's numerical phenotype, i.e., the electronic medical health record and high-resolution medical database of our research center. The ultimate goal is to develop and validate algorithms to detect vital distress in real time, both for inpatient care and outpatient management.

Device for remote and realtime monitoring of neonatal vital signs in neonatal intensive care unit using internet of things: proof-of-concept study

BACKGROUND

Realtime and remote monitoring of neonatal vital signs is a crucial part of providing appropriate care in neonatal intensive care units (NICU) to reduce mortality and morbidity of newborns. In this study, a new approach, a device for remote and real-time monitoring of neonatal vital signs (DRRMNVS) in the neonatal intensive care unit using the internet of things (IoT), was proposed. The system integrates four vital signs: oxygen saturation, pulse rate, body temperature and respiration rate for continuous monitoring using the Blynk app and ThingSpeak IoT platforms.

METHODS

The Wemos D1 mini, a Wi-Fi microcontroller, was used to acquire the four biological biomarkers from sensors, process them and display the result on an OLED display for point of care monitoring and on the Blynk app and ThingSpeak for remote and continuous monitoring of vital signs. The Bland-Altman test was employed to test the agreement of DRRMNVS measurement with reference standards by taking measurements from ten healthy adults.

RESULTS

The prototype of the proposed device was successfully developed and tested. Bias [limits of agreement] were: Oxygen saturation (SpO2): -0.1 [- 1.546 to + 1.346] %; pulse rate: -0.3 [- 2.159 to + 1.559] bpm; respiratory rate: -0.7 [- 0.247 to + 1.647] breaths/min; temperature: 0.21 [+ 0.015˚C to + 0.405˚C] ˚C. The proof-of-concept prototype was developed for $33.19.

CONCLUSION

The developed DRRMNVS device was cheap and had acceptable measurement accuracy of vital signs in a controlled environment. The system has the potential to advance healthcare service delivery for neonates with further development from this proof-of-concept level.

Neonatal Electroencephalogram Electrode-Related Pressure Injury Prevention Quality Improvement Study

OBJECTIVE

To lengthen the days between electroencephalogram electrode-related pressure injury (EERPI) to 100 EERPI-free days in 6 months of study implementation with a goal to maintain 200 EERPI-free days thereafter (≤1 EERPI event/year).

METHODS

This quality improvement study took place in a level IV neonatal ICU over three epochs spanning 2 years: epoch 1 or baseline (January-June 2019), epoch 2 or implementation of intervention (July-December 2019), and epoch 3 or sustainment (January-December 2020). A daily electroencephalogram (EEG) skin assessment tool, introduction in practice of a flexible hydrogel EEG electrode, and successive rapid-cycle staff-education sessions were key interventions of the study.

RESULTS

Seventy-six infants were monitored for 214 continuous EEG (cEEG) days, of which six (13.2%) developed EERPI in epoch 1. Eighty infants were monitored for 193 cEEG days, of which two (2.5%) developed EERPI in epoch 2. One hundred thirty-nine infants were monitored for 338 cEEG days, and none developed EERPI in epoch 3. There was no statistical difference with respect to the median cEEG days among study epochs. A G-chart of EERPI-free days showed an increase in EERPI-free days from an average of 34 days in epoch 1 to 182 days in epoch 2 and 365 days (or zero harm) in epoch 3. Skin erythema from EEG electrodes was noted during the study.

CONCLUSIONS

The structured study interventions eliminated EERPI events in infants monitored with cEEG. Preventive intervention at the cEEG-electrode level coupled with skin assessment successfully reduced EERPIs in neonates.

A Comparative Study of Levetiracetam and Phenobarbital for Neonatal Seizures as a First Line Treatment

Objectives

We aimed to evaluate the use of intravenous levetiracetam as the first-line treatment of neonatal seizures compared with phenobarbital.

Methods

The study was conducted on 104 neonates (0-28 days) with clinical seizures after inclusion criteria. They were assigned in equal ratio into 2 groups; 1 included neonates who received phenobarbitone, and the other included neonates who received levetiracetam. Neonates were loaded with 20 mg/kg of intravenous drug-A (phenobarbitone) or drug-B (levetiracetam). In persistent seizures, a second loading dose of the same drug was given. Crossover to other drugs occurred if seizures persisted after the second dose of the same drug. The proportion of neonates who achieved cessation of seizures following the first or second loading dose of either drug-A or drug-B (PB or LEV) was the main outcome measure provided that they remained free of seizure for the following 24 hours.

Results

After 1 or 2 doses of Levetiracatam or Phenobarbitone, clinical seizures stopped (and remained seizure-free for 24 hours) in 41 (78.84%) and 34 (65.38%) patients, respectively (P = .01). Neonates in the LEV group showed better seizure control than neonates in the PB group (RR = 0.57; 95% CI (0.17, 0.80). We did not report any adverse drug reactions in the LEV group. However, 12 (23.07%) neonates developed adverse drug reactions in the PB Group.

Conclusion

Levetiracetam is considered an effective and safe drug as a first-line AED in neonatal seizures.

Neuromonitoring in neonatal critical care part II: extremely premature infants and critically ill neonates

Neonatal intensive care has expanded from cardiorespiratory care to a holistic approach emphasizing brain health. To best understand and monitor brain function and physiology in the neonatal intensive care unit (NICU), the most commonly used tools are amplitude-integrated EEG, full multichannel continuous EEG, and near-infrared spectroscopy. Each of these modalities has unique characteristics and functions. While some of these tools have been the subject of expert consensus statements or guidelines, there is no overarching agreement on the optimal approach to neuromonitoring in the NICU. This work reviews current evidence to assist decision making for the best utilization of these neuromonitoring tools to promote neuroprotective care in extremely premature infants and in critically ill neonates. Neuromonitoring approaches in neonatal encephalopathy and neonates with possible seizures are discussed separately in the companion paper. IMPACT: For extremely premature infants, NIRS monitoring has a potential role in individualized brain-oriented care, and selective use of aEEG and cEEG can assist in seizure detection and prognostication. For critically ill neonates, NIRS can monitor cerebral perfusion, oxygen delivery, and extraction associated with disease processes as well as respiratory and hypodynamic management. Selective use of aEEG and cEEG is important in those with a high risk of seizures and brain injury. Continuous multimodal monitoring as well as monitoring of sleep, sleep-wake cycling, and autonomic nervous system have a promising role in neonatal neurocritical care.

Challenges and new perspectives of developmental cognitive EEG studies

Despite shared procedures with adults, electroencephalography (EEG) in early development presents many specificities that need to be considered for good quality data collection. In this paper, we provide an overview of the most representative early cognitive developmental EEG studies focusing on the specificities of this neuroimaging technique in young participants, such as attrition and artifacts. We also summarize the most representative results in developmental EEG research obtained in the time and time-frequency domains and use more advanced signal processing methods. Finally, we briefly introduce three recent standardized pipelines that will help promote replicability and comparability across experiments and ages. While this paper does not claim to be exhaustive, it aims to give a sufficiently large overview of the challenges and solutions available to conduct robust cognitive developmental EEG studies.

CARFS7: A guide and proforma for reading a preterm neonate's EEG

OBJECTIVES

The important role of the EEG in preterm and term babies in investigating brain function and seizures, predicting outcomes, evaluating therapeutic interventions and decision-making is being increasingly acknowledged. Development of the brain in the last trimester of pregnancy results in rapid changes in the EEG patterns in this period. Acquiring and interpreting the EEG of a preterm baby can be challenging. The aim of this study was to develop a proforma titled CARFS⁷ (Continuity, Amplitude, Reactivity, Frequency, Synchrony, Symmetry, Sleep, Sharps, Shapes, Size and Seizures) to enable neurologists to read EEGs of premature babies with greater confidence, ease and accuracy and produce a report more easily repeatable and homogenous among operators.

METHODS

The CARFS⁷proforma was developed based on a literature review and the personal experience of the authors. The parameters of the EEG evaluated and scored in the proforma are Continuity, Amplitude, Reactivity/Variability, Frequency, Synchrony, Symmetry, Sleep, Sharps, Shapes/Patterns, Size and Seizures. We also assessed the interrater reliability of the proposed scoring system incorporated in the proforma.

RESULTS

CARFS⁷ proforma incorporates a number of parameters that help evaluate the preterm EEG. The interrater reliability of the proposed scoring system in the CARFS⁷proforma was high.

CONCLUSIONS

CARFS⁷ is a user friendly proforma for reading EEGs in the preterm infant. Interrater reliability using Cohen's k shows high agreement between two child neurologists who independently rated the EEGs of 25 premature babies using this proforma. CARFS⁷ has the potential to provide, accurate, reproducible and valuable information on brain function in the preterm infant in clinical practice.

Measuring respiratory and heart rate using a fiber optic interferometer: A pilot study in a neonate model

INTRODUCTION

The study aim was to test the safety and efficacy of a pad with optic fibers developed for monitoring newborn respiratory rate (RR) and heart rate (HR).

METHODS

Thirty New Zealand White rabbits were included, divided by weight into three groups. RR and HR were measured using two methods for each rabbit: ECG electrodes as the reference method and a newly developed pad with an experimental fiber optic system (EFOS) as the experimental method.

RESULTS

Analysis was performed on data for 29 rabbits (10 female, 34%; 19 male, 66%). EFOS performed better at measuring RR compared with HR. RR values did not differ significantly between the methods for the whole group (p = 0.151) or within each sex (female: p > 0.999; male: p = 0.075). Values for HR, however, did differ between methods for the whole group of animals (p < 0.001) and also within groups by sex (female: p < 0.001; male: p = 0.006).

CONCLUSION

The results of this preclinical study demonstrate the potential of this non-invasive method using a fiber optic pad to measure HR and RR.

Evaluation of the suitability and clinical applicability of different electrodes for aEEG/cEEG monitoring in the extremely premature infant

INTRODUCTION

Monitoring of brain function using continuous electroencephalography (aEEG/cEEG) is an essential tool in the standard care of the term infant, and its use is growing in the premature infant as a biomarker of lesion and brain maturity. However, the placing of the electrodes is a great challenge, particularly in the extremely premature infant, which often discourages neuromonitoring. The aim of this study is to assess the different electrodes available, to select the one that best suits the peculiarities of the extremely premature infant, and evaluate its applicability in clinical practice.

POPULATION AND METHODS

With the aim of designing a neuromonitoring study protocol using aEEG/cEEG in <28 weeks premature infants, an analysis was made of our experience with the type of electrodes available. The electrode that was considered most suitable for this population was chosen by assessing: the need of preparing the scalp, speed in positioning the electrodes, if the application was invasive or not, the possibility of repositioning, risk of skin injuries, sterility of the technique, and durability. The electrode chosen was used for continuous electroencephalographic monitoring started in the first 24 h of life, and maintained until at least 72 h of life.

RESULTS

The electrodes evaluated were: subdermal needles, silver cups, and 2 types of self-adhesive electrodes (solid hydrogel and wet gel). The wet gel electrodes were chosen. They were used on 41 neonates with a mean gestational age of 25.8 ± 1.1 weeks. Good stable impedance was rapidly obtained, without the need of excessive manipulations, and no skin injuries were observed. The satisfaction of the staff involved in positioning them was very high.

CONCLUSION

The self-adhesive disposable electrodes with wet gel and integrated cable enabled the electrodes to be positioned rapidly and provided continuous non-invasive and good quality aEEG/cEEG monitoring in the extremely premature infant.

An Introduction to Neonatal EEG

Newborn care has witnessed significant improvements in survival, but ongoing concerns persist about neurodevelopmental outcome. Protecting the newborn brain is the focus of neurocritical care in the intensive care unit. Brain-focused care places emphasis on clinical practices supporting neurodevelopment in conjunction with early detection, diagnosis, and treatment of brain injury. Technology now facilitates continuous cot-side monitoring of brain function. Neuromonitoring techniques in neonatal intensive care units include the use of electroencephalography (EEG) or amplitude-integrated EEG (aEEG) and near-infrared spectroscopy. This article aims to provide an introduction to EEG, which is appropriate for neonatal healthcare professionals.

Can EEG accurately predict 2-year neurodevelopmental outcome for preterm infants?

OBJECTIVE

Establish if serial, multichannel video electroencephalography (EEG) in preterm infants can accurately predict 2-year neurodevelopmental outcome.

DESIGN AND PATIENTS

EEGs were recorded at three time points over the neonatal course for infants <32 weeks' gestational age (GA). Monitoring commenced soon after birth and continued over the first 3 days. EEGs were repeated at approximately 32 and 35 weeks' postmenstrual age (PMA). EEG scores were based on an age-specific grading scheme. Clinical score of neonatal morbidity risk and cranial ultrasound imaging were completed.

SETTING

Neonatal intensive care unit at Cork University Maternity Hospital, Ireland.

MAIN OUTCOME MEASURES

Bayley Scales of Infant Development III at 2 years' corrected age.

RESULTS

Sixty-seven infants were prospectively enrolled in the study and 57 had follow-up available (median GA 28.9 weeks (IQR 26.5-30.4)). Forty had normal outcome, 17 had abnormal outcome/died. All EEG time points were individually predictive of abnormal outcome; however, the 35-week EEG performed best. The area under the receiver operating characteristic curve (AUC) for this time point was 0.91 (95% CI 0.83 to 1), p<0.001. Comparatively, the clinical course AUC was 0.68 (95% CI 0.54 to 0.80, p=0.015), while abnormal cranial ultrasound was 0.58 (95% CI 0.41 to 0.75, p=0.342).

CONCLUSION

Multichannel EEG is a strong predictor of 2-year outcome in preterm infants particularly when recorded around 35 weeks' PMA. Infants at high risk of brain injury may benefit from early postnatal EEG recording which, if normal, is reassuring. Postnatal clinical complications can contribute to poor outcome; therefore, we state that a later EEG around 35 weeks has a role to play in prognostication.

Non-Contact Automatic Vital Signs Monitoring of Infants in a Neonatal Intensive Care Unit Based on Neural Networks

Infants with fragile skin are patients who would benefit from non-contact vital sign monitoring due to the avoidance of potentially harmful adhesive electrodes and cables. Non-contact vital signs monitoring has been studied in clinical settings in recent decades. However, studies on infants in the Neonatal Intensive Care Unit (NICU) are still limited. Therefore, we conducted a single-center study to remotely monitor the heart rate (HR) and respiratory rate (RR) of seven infants in NICU using a digital camera. The region of interest (ROI) was automatically selected using a convolutional neural network and signal decomposition was used to minimize the noise artefacts. The experimental results have been validated with the reference data obtained from an ECG monitor. They showed a strong correlation using the Pearson correlation coefficients (PCC) of 0.9864 and 0.9453 for HR and RR, respectively, and a lower error rate with RMSE 2.23 beats/min and 2.69 breaths/min between measured data and reference data. A Bland-Altman analysis of the data also presented a close correlation between measured data and reference data for both HR and RR. Therefore, this technique may be applicable in clinical environments as an economical, non-contact, and easily deployable monitoring system, and it also represents a potential application in home health monitoring.

A Hybrid DCNN-SVM Model for Classifying Neonatal Sleep and Wake States Based on Facial Expressions in Video

Sleep is a natural phenomenon controlled by the central nervous system. The sleep-wake pattern, which functions as an essential indicator of neurophysiological organization in the neonatal period, has profound meaning in the prediction of cognitive diseases and brain maturity. In recent years, unobtrusive sleep monitoring and automatic sleep staging have been intensively studied for adults, but much less for neonates. This work aims to investigate a novel video-based unobtrusive method for neonatal sleep-wake classification by analyzing the behavioral changes in the neonatal facial region. A hybrid model is proposed to monitor the sleep-wake patterns of human neonates. The model combines two algorithms: deep convolutional neural network (DCNN) and support vector machine (SVM), where DCNN works as a trainable feature extractor and SVM as a classifier. Data was collected from nineteen Chinese neonates at the Children's Hospital of Fudan University, Shanghai, China. The classification results are compared with the gold standard of video-electroencephalography scored by pediatric neurologists. Validations indicate that the proposed hybrid DCNN-SVM model achieved reliable performances in classifying neonatal sleep and wake states in RGB video frames (with the face region detected), with an accuracy of 93.8 ± 2.2% and an F1-score 0.93 ± 0.3.

Nursing Care During Neonatal Electroencephalographs

BACKGROUND

Electroencephalography (EEG) enables the precise evaluation of a neonate's condition. Three factors that determine the quality of care during this procedure are knowledge, experience, and attitude. The role of the nurse during EEG recordings was evaluated in this study, and the requirements for successfully performing neonatal EEGs, along with practical suggestions, are presented.

METHODS

Evidence in the literature as well as clinical expertise forms the basis for this review.

RESULTS

From our observations and practice during EEGs, we found that the following conditions must be met to successfully perform an EEG examination in a newborn: safety, a period of sleep and calm wakefulness of the neonate, good technical conditions, and no external interferences. Key conditions include the maintenance of safety rules and cooperation between nurses, EEG technicians, and parents.

CONCLUSION

The EEG examinations in neonates weighing less than 1500 g or those requiring respiratory support should only be performed by a trained neonatal intensive care unit nurse.

Deep Learning for EEG Seizure Detection in Preterm Infants

EEG is the gold standard for seizure detection in the newborn infant, but EEG interpretation in the preterm group is particularly challenging; trained experts are scarce and the task of interpreting EEG in real-time is arduous. Preterm infants are reported to have a higher incidence of seizures compared to term infants. Preterm EEG morphology differs from that of term infants, which implies that seizure detection algorithms trained on term EEG may not be appropriate. The task of developing preterm specific algorithms becomes extra-challenging given the limited amount of annotated preterm EEG data available. This paper explores novel deep learning (DL) architectures for the task of neonatal seizure detection in preterm infants. The study tests and compares several approaches to address the problem: training on data from full-term infants; training on data from preterm infants; training on age-specific preterm data and transfer learning. The system performance is assessed on a large database of continuous EEG recordings of 575[Formula: see text]h in duration. It is shown that the accuracy of a validated term-trained EEG seizure detection algorithm, based on a support vector machine classifier, when tested on preterm infants falls well short of the performance achieved for full-term infants. An AUC of 88.3% was obtained when tested on preterm EEG as compared to 96.6% obtained when tested on term EEG. When re-trained on preterm EEG, the performance marginally increases to 89.7%. An alternative DL approach shows a more stable trend when tested on the preterm cohort, starting with an AUC of 93.3% for the term-trained algorithm and reaching 95.0% by transfer learning from the term model using available preterm data. The proposed DL approach avoids time-consuming explicit feature engineering and leverages the existence of the term seizure detection model, resulting in accurate predictions with a minimum amount of annotated preterm data.

Mathematical Analysis of EEG Concordance in Preterm Twin Infants

PURPOSE

Preterm twins are at higher risk of neurodisability than preterm singletons, with monochorionic-diamniotic (MCDA) twins at higher risk than dichorionic-diamniotic (DCDA) twins. The impact of genetic influences on EEG concordance in preterm twins <32 weeks of gestational age is not established. This study aims to investigate EEG concordance in preterm MCDA and dichorionic-diamniotic twins during maturation.

METHODS

Infants <32 weeks of gestational age had multichannel EEG recordings for up to 72 postnatal hours, with repeat recordings at 32 and 35 weeks of postmenstrual age. Twin pairs had synchronous recordings. Mathematical EEG features were generated to represent EEG power, discontinuity, and symmetry. Intraclass correlations, while controlling for gestational age, estimated similarities within twins.

RESULTS

EEGs from 10 twin pairs, 4 MCDA and 6 dichorionic-diamniotic pairs, and 10 age-matched singleton pairs were analyzed from a total of 36 preterm infants. For MCDA twins, 17 of 22 mathematical EEG features had significant (>0.6; P < 0.05) intraclass correlations at one or more time points, compared with 2 of 22 features for DCDA twins and 0 of 22 for singleton pairs. For MCDA twins, all 10 features of discontinuity and all four features of symmetry were significant at one or more time-points. Three features of the MCDA twins (spectral power at 3-8 Hz, EEG skewness at 3-15 Hz, and kurtosis at 3-15 Hz) had significant intraclass correlations over all three time points.

CONCLUSIONS

Preterm twin EEG similarities are subtle but clearly evident through mathematical analysis. MCDA twins showed stronger EEG concordance across different postmenstrual ages, thus confirming a strong genetic influence on preterm EEG activity at this early development stage.

[Evaluation of the suitability and clinical applicability of different electrodes for aEEG/cEEG monitoring in the extremely premature infant]

INTRODUCTION

Monitoring of brain function using continuous electroencephalography (aEEG/cEEG) is an essential tool in the standard care of the term infant, and its use is growing in the premature infant as a biomarker of lesion and brain maturity. However, the placing of the electrodes is a great challenge, particularly in the extremely premature infant, which often discourages neuromonitoring. The aim of this study is to assess the different electrodes available, to select the one that best suits the peculiarities of the extremely premature infant, and evaluate its applicability in clinical practice.

POPULATION AND METHODS

With the aim of designing a neuromonitoring study protocol using aEEG/cEEG in<28 weeks premature infants, an analysis was made of our experience with the type of electrodes available. The electrode that was considered most suitable for this population was chosen by assessing: the need of preparing the scalp, speed in positioning the electrodes, if the application was invasive or not, the possibility of repositioning, risk of skin injuries, sterility of the technique, and durability. The electrode chosen was used for continuous electroencephalographic monitoring started in the first 24h of life, and maintained until at least 72h of life.

RESULTS

The electrodes evaluated were: subdermal needles, silver cups, and 2 types of self-adhesive electrodes (solid hydrogel and wet gel). The wet gel electrodes were chosen. They were used on 41 neonates with a mean gestational age of 25.8±1.1 weeks. Good stable impedance was rapidly obtained, without the need of excessive manipulations, and no skin injuries were observed. The satisfaction of the staff involved in positioning them was very high.

CONCLUSION

The self-adhesive disposable electrodes with wet gel and integrated cable enabled the electrodes to be positioned rapidly and provided continuous non-invasive and good quality aEEG/cEEG monitoring in the extremely premature infant.

Non-contact physiological monitoring of preterm infants in the Neonatal Intensive Care Unit

The implementation of video-based non-contact technologies to monitor the vital signs of preterm infants in the hospital presents several challenges, such as the detection of the presence or the absence of a patient in the video frame, robustness to changes in lighting conditions, automated identification of suitable time periods and regions of interest from which vital signs can be estimated. We carried out a clinical study to evaluate the accuracy and the proportion of time that heart rate and respiratory rate can be estimated from preterm infants using only a video camera in a clinical environment, without interfering with regular patient care. A total of 426.6 h of video and reference vital signs were recorded for 90 sessions from 30 preterm infants in the Neonatal Intensive Care Unit (NICU) of the John Radcliffe Hospital in Oxford. Each preterm infant was recorded under regular ambient light during daytime for up to four consecutive days. We developed multi-task deep learning algorithms to automatically segment skin areas and to estimate vital signs only when the infant was present in the field of view of the video camera and no clinical interventions were undertaken. We propose signal quality assessment algorithms for both heart rate and respiratory rate to discriminate between clinically acceptable and noisy signals. The mean absolute error between the reference and camera-derived heart rates was 2.3 beats/min for over 76% of the time for which the reference and camera data were valid. The mean absolute error between the reference and camera-derived respiratory rate was 3.5 breaths/min for over 82% of the time. Accurate estimates of heart rate and respiratory rate could be derived for at least 90% of the time, if gaps of up to 30 seconds with no estimates were allowed.

A standardised assessment scheme for conventional EEG in preterm infants

OBJECTIVE

To develop a standardised scheme for assessing normal and abnormal electroencephalography (EEG) features of preterm infants. To assess the interobserver agreement of this assessment scheme.

METHODS

We created a standardised EEG assessment scheme for 6 different post-menstrual age (PMA) groups using 4 EEG categories. Two experts, not involved in the development of the scheme, evaluated this on 24 infants <32 weeks gestational age (GA) using random 2 hour EEG epochs. Where disagreements were found, the features were checked and modified. Finally, the two experts independently evaluated 2 hour EEG epochs from an additional 12 infants <37 weeks GA. The percentage of agreement was calculated as the ratio of agreements to the sum of agreements plus disagreements.

RESULTS

Good agreement in all patients and EEG feature category was obtained, with a median agreement between 80% and 100% over the 4 EEG assessment categories. No difference was found in agreement rates between the normal and abnormal features (p = 0.959).

CONCLUSIONS

We developed a standard EEG assessment scheme for preterm infants that shows good interobserver agreement.

SIGNIFICANCE

This will provide information to Neonatal Intensive Care Unit (NICU) staff about brain activity and maturation. We hope this will prove useful for many centres seeking to use neuromonitoring during critical care for preterm infants.

System Level Framework for Assessing the Accuracy of Neonatal EEG Acquisition

Significant research has been conducted in recent years to design low-cost alternatives to the current EEG monitoring systems used in healthcare facilities. Testing such systems on a vulnerable population such as newborns is complicated due to ethical and regulatory considerations that slow down the technical development. This paper presents and validates a method for quantifying the accuracy of neonatal EEG acquisition systems and electrode technologies via clinical data simulations that do not require neonatal participants. The proposed method uses an extensive neonatal EEG database to simulate analogue signals, which are subsequently passed through electrical models of the skin-electrode interface, which are developed using wet and dry EEG electrode designs. The signal losses in the system are quantified at each stage of the acquisition process for electrode and acquisition board losses. SNR, correlation and noise values were calculated. The results verify that low-cost EEG acquisition systems are capable of obtaining clinical grade EEG. Although dry electrodes result in a significant increase in the skin-electrode impedance, accurate EEG recordings are still achievable.

EEG for the assessment of neurological function in newborn infants immediately after birth

OBJECTIVE

To assess the neurological function of newborn infants in the first minutes after birth using EEG.

DESIGN AND PATIENTS

We obtained electroencephalography (EEG) recordings in term infants following elective caesarean section. After delivery, disposable EEG electrodes were attached to the infants' scalp over the frontal and central regions bilaterally and EEG was recorded for 10 min. Both visual and quantitative measures were used to analyse the EEGs.

SETTING

The operative delivery theatre of Cork University Maternity Hospital, Ireland.

RESULTS

Forty-nine infants had EEG recordings over the frontal and central regions. The median (IQR) age at time of initial EEG recording was 3.0 (2.5-3.8) min. While movement artefact contaminated parts of many recordings, good-quality EEG, with mixed-frequency activity with a range of 25-50 μV, was observed in all infants. The majority of EEG spectral power was within the delta band: the median (IQR) relative delta power was 87.8% (83.7%-90%). Almost all (95%) spectral power was below a median (IQR) of 7.56 Hz (6.17-9.76 Hz).

CONCLUSIONS

EEG recording is very feasible in the immediate newborn period. This study provides valuable objective information about neurological function during this transitional period.

Successful Reduction in Electrode-Related Pressure Ulcers During EEG Monitoring in Critically Ill Neonates

BACKGROUND

Neonates are at a high risk for pressure ulcers (PU) due to skin immaturity and exposure to various medical devices. The prevalence of PU in the neonatal intensive care unit is estimated to be 23%, with 80% of those being related to medical devices, including electroencephalographic (EEG) electrodes. Proposed mechanisms involve prolonged pressure to the electrodes and chemical reactions to conductive agents.

PURPOSE

The object of this quality improvement project was to reduce PU in neonates during continuous EEG (cEEG) monitoring by 50% within 12 months and 75% within 18 months. A secondary objective was to eliminate electrode-related infections by 12 months. Balancing measures included gestational age at the time of monitoring, integrity of the EEG setup, and cost effectiveness. The process measure was adherence to the skin-monitoring tool kit.

METHODS

A multiple Plan-Do-Study-Act cycle method was used. All neonates monitored with cEEG were included. The monitoring tool kit was used to document the condition of scalp and EEG electrodes before, during, and after cEEG.

RESULTS

In the preproject period, 8.5% (9/106) of monitored patients developed PU, and 22.2% (2/9) of those developed infections. During the project period, 3.5% (7/198) of monitored patients developed PU and no infections were observed. During monitoring, 21 patients showed skin irritation, and timely intervention resulted in resolution in more than 90% of the cases and prevented progression into PU. Silver/silver chloride-plated electrodes, when exposed to external heat sources, can cause burns, resembling PU.

IMPLICATIONS FOR PRACTICE

Intervention at the electrode level together with skin inspection successfully reduces PU in neonates. Silver/silver chloride-plated electrodes should be avoided in neonates.

IMPLICATIONS FOR RESEARCH

Further research is needed to identify the optimal electrode for neonatal EEG.

Analysis of a Low-Cost EEG Monitoring System and Dry Electrodes toward Clinical Use in the Neonatal ICU

Electroencephalography (EEG) is an important clinical tool for monitoring neurological health. However, the required equipment, expertise, and patient preparation inhibits its use outside of tertiary care. Non-experts struggle to obtain high-quality EEG due to its low amplitude and artefact susceptibility. Wet electrodes are currently used, which require abrasive/conductive gels to reduce skin-electrode impedance. Advances in dry electrodes, which do not require gels, have simplified this process. However, the assessment of dry electrodes on neonates is limited due to health and safety barriers. This study presents a simulation framework for assessing the quality of EEG systems using a neonatal EEG database, without the use of human participants. The framework is used to evaluate a low-cost EEG acquisition system and compare performance of wet and dry (Micro Transdermal Interface Platforms (MicroTIPs), g.tec-g.SAHARA) electrodes using accurately acquired impedance models. A separate experiment assessing the electrodes on adult participants was conducted to verify the simulation framework’s efficacy. Dry electrodes have higher impedance than wet electrodes, causing a reduction in signal quality. However, MicroTIPs perform comparably to wet electrodes at the frontal region and g.tec-g.SAHARA performs well at the occipital region. Using the simulation framework, a 25dB signal-to-noise ratio (SNR) was obtained for the low-cost EEG system. The tests on adults closely matched the simulated results.

Clamping the Umbilical Cord in Premature Deliveries (CUPiD): Neuromonitoring in the Immediate Newborn Period in a Randomized, Controlled Trial of Preterm Infants Born at <32 Weeks of Gestation

OBJECTIVE

To compare cerebral activity and oxygenation in preterm infants (<32 weeks of gestation) randomized to different cord clamping strategies.

STUDY DESIGN

Preterm infants born at <32 weeks of gestation were randomized to immediate cord clamping, umbilical cord milking (cord stripped 3 times), or delayed cord clamping for 60 seconds with bedside resuscitation. All infants underwent electroencephalogram (EEG) and cerebral near infrared spectroscopy for the first 72 hours after birth. Neonatal primary outcome measures were quantitative measures of the EEG (17 features) and near infrared spectroscopy over 1-hour time frames at 6 and 12 hours of life.

RESULTS

Forty-five infants were recruited during the study period. Twelve infants (27%) were randomized to immediate cord clamping, 19 (42%) to umbilical cord milking, and 14 (31%) to delayed cord clamping with bedside resuscitation. There were no significant differences between groups for measures of EEG activity or cerebral near infrared spectroscopy. Three of the 45 infants (6.7%) were diagnosed with severe IVH (2 in the immediate cord clamping group, 1 in the umbilical cord milking group; P = .35).

CONCLUSIONS

There were no differences in cerebral EEG activity and cerebral oxygenation values between cord management strategies at 6 and 12 hours.

TRIAL REGISTRATION

ISRCTN92719670.

Light-cured polymer electrodes for non-invasive EEG recordings

We invented the first non-metallic, self-adhesive and dry biosignalling electrode. The PEDOT polymer electrode changes its aggregate state and conductivity by a light curing procedure. The electrode can be applied as a gel underneath hair without shaving. With the aid of blue light, the electrode can be hardened within a few seconds at the desired location on the scalp. The cured polymer electrode is highly conductive and can be applied on a very small location. Unlike other EEG electrodes, our electrode does not lose conductivity upon drying. Furthermore, our electrode strongly bonds to skin and does not require any additional adhesive. Short circuits due to an outflow of gel are prevented with this technique. Therefore, the PEDOT polymer electrode is extremely well suited for applications that, up to now, have been challenging, such as non-invasive EEG recordings from awake and freely moving animals, EEG recordings from preterm babies in the neonatal intensive care unit or long-term recordings in the case of sleep monitoring or epilepsy diagnostics. We addressed two technical questions in this work. First, is the EEG recorded with polymer electrodes comparable to a standard EEG? Second, is it possible to record full-band EEGs with our electrodes?

Noninvasive EEG Recordings from Freely Moving Piglets

The method allows the recording of high-quality electroencephalograms (EEGs) from freely moving piglets directly in the pigpen. We use a one-channel telemetric electroencephalography system in combination with standard self-adhesive hydrogel electrodes. The piglets are calmed down without the use of sedatives. After their release into the pigpen, the piglets behave normally-they drink and sleep in the same cycle as their siblings. Their sleep phases are used for the EEG recordings.

Long term electroencephalography in preterm neonates: Safety and quality of electrode types

OBJECTIVES

The objective of this study was to compare gold cup and hydrogel electrodes for frequency of electrode replacement, longevity of the original electrodes after initial placement, recording quality, and skin safety issues in long-term EEG studies in preterm neonates.

METHODS

We performed a prospective trial with newborns born at ≥23 weeks and ≤30 weeks of gestational age (GA). Two mirror image EEG electrode arrays were utilized on consecutive subjects, where gold cup electrodes alternated with hydrogel electrodes.

RESULTS

Our sample included 50 neonates with mean GA of 27 (±1) weeks. The mean recording time was 84 (±15) hours. No difference was present in the frequency of replacement of either type across the total recording time (p = 0.8). We collected the time at which electrodes were first replaced, and found that hydrogel electrodes showed a longer uninterrupted recording time of 28(±2) hours vs. 20(±2) hours for gold cup electrodes (p = 0.01). Recording quality was similar in either type (p = 0.2). None of the patients experienced significant skin irritation from a discrete electrode.

CONCLUSION

Long-term EEG studies can be performed with either gold cup or hydrogel electrodes, validating the safety and quality of both electrode types.

SIGNIFICANCE

Hydrogel electrodes are a reasonable alternative for use in long-term EEG studies in preterm neonates.

A review of important electroencephalogram features for the assessment of brain maturation in premature infants

This review describes the maturational features of the baseline electroencephalogram (EEG) in the neurologically healthy preterm infant. Features such as continuity, sleep state, synchrony and transient waveforms are described, even from extremely preterm infants and includes abundant illustrated examples. The physiological significance of these EEG features and their relationship to neurodevelopment are highlighted where known. This review also demonstrates the importance of multichannel conventional EEG monitoring for preterm infants as many of the features described are not apparent if limited channel EEG monitors are used.

CONCLUSION

This review aims to provide healthcare professionals in the neonatal intensive care unit with guidance on the more common normal maturational features seen in the EEG of preterm infants.

Electrographic Seizures during the Early Postnatal Period in Preterm Infants

OBJECTIVE

To investigate the frequency and characteristics of electrographic seizures in preterm infants in the early postnatal period.

STUDY DESIGN

Infants <32 weeks gestational age (GA) (n = 120) were enrolled for continuous multichannel electroencephalography (EEG) recording initiated as soon as possible after birth and continued for approximately up to 72 hours of age. Electrographic seizures were identified visually, annotated, and analyzed. Quantitative descriptors of the temporal evolution of seizures, including total seizure burden, seizure duration, and maximum seizure burden, were calculated.

RESULTS

Median GA was 28.9 weeks (IQR, 26.6-30.3 weeks) and median birth weight was 1125 g (IQR, 848-1440 g). Six infants (5%; 95% CI, 1.9-10.6%) had electrographic seizures. Median total seizure burden, seizure duration, and maximum seizure burden were 40.3 minutes (IQR, 5.0-117.5 minutes), 49.6 seconds (IQR, 43.4-76.6 seconds), and 10.8 minutes/hour (IQR, 1.6-20.2 minutes/hour), respectively. Seizure burden was highest in 2 infants with significant abnormalities on neuroimaging.

CONCLUSION

Electrographic seizures are infrequent within the first few days of birth in very preterm infants. Seizures in this population are difficult to detect accurately without continuous multichannel EEG monitoring.

Lost in Transition: A Systematic Review of Neonatal Electroencephalography in the Delivery Room-Are We Forgetting an Important Biomarker for Newborn Brain Health?

BACKGROUND

Electroencephalography (EEG) monitoring is routine in neonatal intensive care units (NICUs) for detection of seizures, neurological monitoring of infants following perinatal asphyxia, and increasingly, following preterm delivery. EEG monitoring is not routinely commenced in the delivery room (DR).

OBJECTIVES

To determine the feasibility of recording neonatal EEG in the DR, and to assess its usefulness as a marker of neurological well-being during immediate newborn transition.

METHODS

We performed a systematic stepwise search of PubMed using the following terms: infant, newborns, neonate, DR, afterbirth, transition, and EEG. Only human studies describing EEG monitoring in the first 15 min following delivery were included. Infants of all gestational ages were included.

RESULTS

Two original studies were identified that described EEG monitoring of newborn infants within the DR. Both prospective observational studies used amplitude-integrated EEG (aEEG) monitoring and found it feasible in infants >34 weeks' gestation; however, technical challenges made it difficult to obtain continuous reliable data. Different EEG patterns were identified in uncompromised newborns and those requiring resuscitation.

CONCLUSION

EEG monitoring is possible in the DR and may provide an objective baseline measure of neurological function. Further feasibility studies are required to overcome technical challenges in the DR, but these challenges are not insurmountable with modern technology.

Predicting 2-y outcome in preterm infants using early multimodal physiological monitoring

BACKGROUND

Preterm infants are at risk of adverse outcome. The aim of this study is to develop a multimodal model, including physiological signals from the first days of life, to predict 2-y outcome in preterm infants.

METHODS

Infants <32 wk gestation had simultaneous multi-channel electroencephalography (EEG), peripheral oxygen saturation (SpO2), and heart rate (HR) monitoring. EEG grades were combined with gestational age (GA) and quantitative features of HR and SpO2 in a logistic regression model to predict outcome. Bayley Scales of Infant Development-III assessed 2-y neurodevelopmental outcome. A clinical course score, grading infants at discharge as high or low morbidity risk, was used to compare performance with the model.

RESULTS

Forty-three infants were included: 27 had good outcomes, 16 had poor outcomes or died. While performance of the model was similar to the clinical course score graded at discharge, with an area under the receiver operator characteristic (AUC) of 0.83 (95% confidence intervals (CI): 0.69-0.95) vs. 0.79 (0.66-0.90) (P = 0.633), the model was able to predict 2-y outcome days after birth.

CONCLUSION

Quantitative analysis of physiological signals, combined with GA and graded EEG, shows potential for predicting mortality or delayed neurodevelopment at 2 y of age.