Remote data collection of infant activity and sleep patterns via wearable sensors in the HEALthy Brain and Child Development Study (HBCD).

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. Wearable and remote sensing technologies have advanced data collection outside of laboratory settings to enable exploring, in more detail, the associations of early experiences with brain development and social and health outcomes. In the HBCD Study, the Novel Technology/Wearable Sensors Working Group (WG-NTW) identified two primary data types to be collected: infant activity (by measuring leg movements) and sleep (by measuring heart rate and leg movements). These wearable technologies allow for remote collection in the natural environment. This paper illustrates the collection of such data via wearable technologies and describes the decision-making framework, which led to the currently deployed study design, data collection protocol, and derivatives, which will be made publicly available. Moreover, considerations regarding actual and potential challenges to adoption and use, data management, privacy, and participant burden were examined. Lastly, the present limitations in the field of wearable sensor data collection and analysis will be discussed in terms of extant validation studies, the difficulties in comparing performance across different devices, and the impact of evolving hardware/software/firmware.

The development and structure of the HEALthy Brain and Child Development (HBCD) Study EEG protocol.

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. Electroencephalography (EEG) is one of two brain imaging modalities central to the HBCD Study. EEG records electrical signals from the scalp that reflect electrical brain activity. In addition, the EEG signal can be synchronized to the presentation of discrete stimuli (auditory or visual) to measure specific cognitive processes with excellent temporal precision (e.g., event-related potentials; ERPs). EEG is particularly helpful for the HBCD Study as it can be used with awake, alert infants, and can be acquired continuously across development. The current paper reviews the HBCD Study's EEG/ERP protocol: (a) the selection and development of the tasks (Video Resting State, Visual Evoked Potential, Auditory Oddball, Face Processing); (b) the implementation of common cross-site acquisition parameters and hardware, site setup, training, and initial piloting; (c) the development of the preprocessing pipelines and creation of derivatives; and (d) the incorporation of equity and inclusion considerations. The paper also provides an overview of the functioning of the EEG Workgroup and the input from members across all steps of protocol development and piloting.

Clinical characteristics, longitudinal adaptive functioning, and association with electroencephalogram activity in PPP2R5D-related neurodevelopmental disorder.

Protein phosphatase 2 regulatory subunit B56δ related neurodevelopmental disorder (PPP2R5D-related NDD) is largely caused by de novo heterozygous missense PPP2R5D variants. We report medical characteristics, longitudinal adaptive functioning, and in-person neurological, motor, cognitive, and electroencephalogram (EEG) activity for PPP2R5D-related NDD. Forty-two individuals (median age 6 years, range = 0.8-25.3) with pathogenic/likely pathogenic PPP2R5D variants were assessed, and almost all variants were missense (97.6%) and de novo (85.7%). Common clinical symptoms were developmental delay, hypotonia, macrocephaly, seizures, autism, behavioral challenges, and sleep problems. The mean Gross motor functional measure-66 was 60.2 ± 17.3% and the mean Revised upper limb module score was 25.9 ± 8.8. The Vineland-3 adaptive behavior composite score (VABS-3 ABC) at baseline was low (M = 61.7 ± 16.8). VABS-3 growth scale value scores increased from baseline in all subdomains (range = 0.6-5.9) after a mean follow-up of 1.3 ± 0.3 years. EEG beta and gamma power were negatively correlated with VABS-3 score; p < 0.05. Individuals had a mean Quality-of-life inventory-disability score of 74.7 ± 11.4. Twenty caregivers (80%) had a risk of burnout based on the Caregiver burden inventory. Overall, the most common clinical manifestations of PPP2R5D-related NDD were impaired cognitive, adaptive function, and motor skills; and EEG activity was associated with adaptive functioning. This clinical characterization describes the natural history in preparation for clinical trials.

Combining developmental and sleep health measures for autism spectrum disorder screening: an ECHO study.

BACKGROUND: Sleep problems are reported for up to 80% of autistic individuals. We examined whether parsimonious sets of items derived from the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) and the Brief Infant Sleep Questionnaire (BISQ) are superior to the standard M-CHAT-R in predicting subsequent autism spectrum disorder (ASD) diagnoses. METHODS: Participants from 11 Environmental influences on Child Health Outcomes (ECHO) cohorts were included. We performed logistic LASSO regression models with 10-fold cross-validation to identify whether a combination of items derived from the M-CHAT-R and BISQ are superior to the standard M-CHAT-R in predicting ASD diagnoses. RESULTS: The final sample comprised 1552 children. The standard M-CHAT-R had a sensitivity of 44% (95% CI: 34, 55), specificity of 92% (95% CI: 91, 94), and AUROC of 0.726 (95% CI: 0.663, 0.790). A higher proportion of children with ASD had difficulty falling asleep or resisted bedtime during infancy/toddlerhood. However, LASSO models revealed parental reports of sleep problems did not improve the accuracy of the M-CHAT-R in predicting ASD diagnosis. CONCLUSION: While children with ASD had higher rates of sleep problems during infancy/toddlerhood, there was no improvement in ASD developmental screening through the incorporation of parent-report sleep metrics. IMPACT: Parental-reported sleep problems are common in autism spectrum disorder (ASD). We investigated whether the inclusion of parental-reports of infant/toddler sleep patterns enhanced the effectiveness of developmental screening for autism. We reported higher rates of difficulty falling asleep and resisting bedtime during infancy and toddlerhood among children later diagnosed with ASD; however, we did not find an improvement in ASD developmental screening through the incorporation of parent-report sleep metrics. In our sample, the standard M-CHAT-R had a sensitivity of 39% among children of mothers with government insurance compared with a sensitivity of 53% among children of mothers with employer-based insurance.

Longitudinal effects of prenatal alcohol exposure on visual neurodevelopment over infancy.

Prenatal alcohol exposure (PAE) affects neurodevelopment in over 59 million individuals globally. Prior studies using dichotomous categorization of alcohol use and comorbid substance exposures provide limited knowledge of how prenatal alcohol specifically impacts early human neurodevelopment. In this longitudinal cohort study from Cape Town, South Africa, PAE is measured continuously-characterizing timing, dose, and drinking patterns (i.e., binge drinking). High-density electroencephalography (EEG) during a visual-evoked potential (VEP) task was collected from infants aged 8 to 52 weeks with prenatal exposure exclusively to alcohol and matched on sociodemographic factors to infants with no substance exposure in utero. First trimester alcohol exposure related to altered timing of the P1 VEP component over the first 6 months postnatally, and first trimester binge drinking exposure altered timing of the P1 VEP components such that increased exposure was associated with longer VEP latencies while increasing age was related to shorter VEP latencies (n = 108). These results suggest alcohol exposure in the first trimester may alter visual neurodevelopmental timing in early infancy. Exploratory individual-difference analysis across infants with and without PAE tested the relation between VEP latencies and myelination for a subsample of infants with usable magnetic resonance imaging (MRI) T1w and T2w scans collected at the same time point as EEG (n = 47). Decreased MRI T1w/T2w ratios (an indicator of myelin) in the primary visual cortex (n = 47) were linked to longer P1 VEP latencies. Results from these two sets of analyses suggest that prenatal alcohol and postnatal myelination may both separately impact VEP latency over infancy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

In Utero Exposure to Alcohol and Tobacco and Electroencephalogram Power During Childhood.

Importance: Prenatal alcohol exposure (PAE) and prenatal tobacco exposure (PTE) are risk factors associated with adverse neurobehavioral and cognitive outcomes. Objective: To quantify long-term associations of PAE and PTE with brain activity in early and middle childhood via electroencephalography (EEG). Design, Setting, and Participants: This cohort study included participants enrolled in the Safe Passage Study (August 2007 to January 2015), from which a subset of 649 participants were followed up in the Environmental Influences on Child Health Outcomes Program. From September 2018 through November 2022, EEG recordings were obtained at ages 4, 5, 7, 9, or 11 years. Data were analyzed from November 2022 to November 2023. Exposures: Maternal self-reported consumptions of alcohol and tobacco during pregnancy were captured at the recruitment interview and at up to 3 visits during pregnancy (20-24, 28-32, and ≥34 weeks' gestation). Classifications of PAE (continuous drinking, quit-early drinking, and nondrinking) and PTE (continuous smoking, quit-early smoking, and nonsmoking) were previously obtained. Main Outcomes and Measures: EEG band powers (theta, alpha, beta, gamma) were extracted from the EEG recordings. Linear regression models were used to estimate the associations of PAE and PTE with EEG estimates. Results: The final sample included 649 participants (333 [51.3%] female) aged 4, 5, 7, 9, or 11 years. Children whose mothers were in the quit-early drinking cluster had increased alpha power (0.116 [95% CI, 0.023 to 0.209] µV2; P = .02) compared with individuals without PAE. The magnitude of this increase was approximately double for children exposed to continuous drinking (0.211 [95% CI, 0.005 to 0.417] µV2; P = .04). Children whose mothers were in the continuous smoking cluster had decreased beta power (-0.031 [95% CI, -0.059 to -0.003] µV2; P = .03) and gamma power (-0.020 [95% CI, -0.039 to -0.000] µV2; P = .04) compared with the nonsmoking cluster. In exploratory sex-stratified models, male participants in the quit-early PAE cluster had greater EEG power in the alpha band (0.159 [95% CI, 0.003 to 0.315] µV2; P = .04) compared with those with no PAE, and the difference was approximately double for male participants with continuous PAE (0.354 [95% CI, 0.041 to 0.667] µV2; P = .03). Male participants in the continuous PTE cluster had decreased beta (-0.048 [95% CI, -0.090 to - 0.007] µV2; P = .02) and gamma (-0.032 [95% CI, -0.061 - 0.002] µV2; P = .04) power compared with those with no PTE. Conclusions and Relevance: These findings suggest that even low levels of PAE and PTE were associated with long-term alterations of brain activity.

Neonatal rhinorrhea, heart rate variability, and childhood exercise-induced wheeze.

Background: There is increasing evidence linking infant rhinorrhea to school-age exercise-induced wheeze (EIW) via a parasympathetic nervous system pathway. The ratio of the root mean square of successive differences in heart beats (RMSSD) measured in quiet sleep versus active sleep (RMSSDQS:AS) is a novel biomarker in asthma. Objective: We tested the hypotheses that (1) neonatal rhinorrhea predicts childhood EIW independent of other neonatal respiratory symptoms, (2) neonatal RMSSDQS:AS predicts childhood EIW, and (3) RMSSDQS:AS mediates the association between neonatal rhinorrhea and childhood EIW. Methods: Participants from the Safe Passage/Environmental Influences on Child Health Outcomes (PASS/ECHO) prospective birth cohort had heart rate variability extracted from electrocardiogram traces acquired in the first month of life. Parents reported on rhinorrhea in their child at age 1 month and on EIW in their child at ages 4 to 11 years. Results: In models (N = 831) adjusted for potential confounders and covariates, including neonatal wheeze, cough and fever, neonatal rhinorrhea-predicted childhood EIW (relative risk [RR] = 2.22; P = .040), specifically, among females (RR = 3.38; P = .018) but not males (RR = 1.39; P = .61). Among participants contributing data in both active and quiet sleep (n = 231), RMSSDQS:AS predicted EIW (RR = 2.36; P = .003) and mediated the effect estimate of neonatal rhinorrhea predicting EIW among females. Half of the females with a higher RMSSDQS:AS and neonatal rhinorrhea (n = 5 of 10) developed EIW as compared with 1.8% of the other females (n = 2 of 109) (P < .001). Conclusions: Our findings support dysregulation of the parasympathetic nervous system in infancy as one of the possible underlying mechanisms for the development of EIW later in childhood among females, which could aid in the development of future interventions.

Dopamine transporter blockade during adolescence increases adult dopamine function, impulsivity, and aggression.

Sensitive developmental periods shape neural circuits and enable adaptation. However, they also engender vulnerability to factors that can perturb developmental trajectories. An understanding of sensitive period phenomena and mechanisms separate from sensory system development is still lacking, yet critical to understanding disease etiology and risk. The dopamine system is pivotal in controlling and shaping adolescent behaviors, and it undergoes heightened plasticity during that time, such that interference with dopamine signaling can have long-lasting behavioral consequences. Here we sought to gain mechanistic insight into this dopamine-sensitive period and its impact on behavior. In mice, dopamine transporter (DAT) blockade from postnatal (P) day 22 to 41 increases aggression and sensitivity to amphetamine (AMPH) behavioral stimulation in adulthood. Here, we refined this sensitive window to P32-41 and identified increased firing of dopaminergic neurons in vitro and in vivo as a neural correlate to altered adult behavior. Aggression can result from enhanced impulsivity and cognitive dysfunction, and dopamine regulates working memory and motivated behavior. Hence, we assessed these behavioral domains and found that P32-41 DAT blockade increases impulsivity but has no effect on cognition, working memory, or motivation in adulthood. Lastly, using optogenetics to drive dopamine neurons, we find that increased VTA but not SNc dopaminergic activity mimics the increase in impulsive behavior in the Go/NoGo task observed after adolescent DAT blockade. Together our data provide insight into the developmental origins of aggression and impulsivity that may ultimately improve diagnosis, prevention, and treatment strategies for related neuropsychiatric disorders.

A comprehensive wireless neurological and cardiopulmonary monitoring platform for pediatrics.

Neurodevelopment in the first 10 years of life is a critical time window during which milestones that define an individual's functional potential are achieved. Comprehensive multimodal neurodevelopmental monitoring is particularly crucial for socioeconomically disadvantaged, marginalized, historically underserved and underrepresented communities as well as medically underserved areas. Solutions designed for use outside the traditional clinical environment represent an opportunity for addressing such health inequalities. In this work, we present an experimental platform, ANNE EEG, which adds 16-channel cerebral activity monitoring to the existing, USA FDA-cleared ANNE wireless monitoring platform which provides continuous electrocardiography, respiratory rate, pulse oximetry, motion, and temperature measurements. The system features low-cost consumables, real-time control and streaming with widely available mobile devices, and fully wearable operation to allow a child to remain in their naturalistic environment. This multi-center pilot study successfully collected ANNE EEG recordings from 91 neonatal and pediatric patients at academic quaternary pediatric care centers and in LMIC settings. We demonstrate the practicality and feasibility to conduct electroencephalography studies with high levels of accuracy, validated via both quantitative and qualitative metrics, compared against gold standard systems. An overwhelming majority of parents surveyed during studies indicated not only an overall preference for the wireless system, but also that its use would improve their children's physical and emotional health. Our findings demonstrate the potential for the ANNE system to perform multimodal monitoring to screen for a variety of neurologic diseases that have the potential to negatively impact neurodevelopment.

Maternal hair cortisol predicts periodic and aperiodic infant frontal EEG activity longitudinally across infancy.

Maternal stress is known to be an important factor in shaping child development, yet the complex pattern of associations between stress and infant brain development remains understudied. To better understand the nuanced relations between maternal stress and infant neurodevelopment, research investigating longitudinal relations between maternal chronic physiological stress and infant brain function is warranted. In this study, we leveraged longitudinal data to disentangle between- from within-person associations of maternal hair cortisol and frontal electroencephalography (EEG) power at three time points across infancy at 3, 9, and 15 months. We analyzed both aperiodic power spectral density (PSD) slope and traditional periodic frequency band activity. On the within-person level, maternal hair cortisol was associated with a flattening of frontal PSD slope and an increase in relative frontal beta. However, on the between-person level, higher maternal hair cortisol was associated with steeper frontal PSD slope, increased relative frontal theta, and decreased relative frontal beta. The within-person findings may reflect an adaptive neural response to relative shifts in maternal stress levels, while the between-person results demonstrate the potentially detrimental effects of chronically elevated maternal stress. This analysis offers a novel, quantitative insight into the relations between maternal physiological stress and infant cortical function.

Association of Gestational Diabetes Mellitus and Perinatal Maternal Depression with Early Childhood Behavioral Problems: An Environmental Influences on Child Health Outcomes (ECHO) Study.

This study examined the association of gestational diabetes mellitus (GDM), prenatal, and postnatal maternal depressive symptoms with externalizing, internalizing, and autism spectrum problems on the Preschool Child Behavior Checklist in 2379 children aged 4.12 ± 0.60 (48% female; 47% White, 32% Black, 15% Mixed Race, 4% Asian, <2% American Indian/Alaskan Native, <2% Native Hawaiian; 23% Hispanic). Data were collected from the NIH Environmental influences on Child Health Outcomes (ECHO) Program from 2009-2021. GDM, prenatal, and postnatal maternal depressive symptoms were each associated with increased child externalizing and internalizing problems. GDM was associated with increased autism behaviors only among children exposed to perinatal maternal depressive symptoms above the median level. Stratified analyses revealed a relation between GDM and child outcomes in males only.

Age-related trends in aperiodic EEG activity and alpha oscillations during early- to middle-childhood.

Age-related structural and functional changes that occur during brain development are critical for cortical development and functioning. Previous electroencephalography (EEG) and magnetoencephalography (MEG) studies have highlighted the utility of power spectra analyses and have uncovered age-related trends that reflect perceptual, cognitive, and behavioural states as well as their underlying neurophysiology. The aim of the current study was to investigate age-related change in aperiodic and periodic alpha activity across a large sample of pre- and school-aged children (N = 502, age range 4 -11-years-of-age). Power spectra were extracted from baseline EEG recordings (eyes closed, eyes open) for each participant and parameterized into aperiodic activity to derive the offset and exponent parameters and periodic alpha oscillatory activity to derive the alpha peak frequency and the associated power estimates. Multilevel models were run to investigate age-related trends and condition-dependent changes for each of these measures. We found quadratic age-related effects for both the aperiodic offset and exponent. In addition, we observed increases in periodic alpha peak frequency as a function of age. Aperiodic measures and periodic alpha power were larger in magnitude during eyes closed compared to the eyes open baseline condition. Taken together, these results advance our understanding of the maturational patterns/trajectories of brain development during early- to middle-childhood.

Longitudinal characterization of EEG power spectra during eyes open and eyes closed conditions in children.

This study is the first to examine spectrum-wide (1 to 250 Hz) differences in electroencephalogram (EEG) power between eyes open (EO) and eyes closed (EC) resting state conditions in 486 children. The results extend the findings of previous studies by characterizing EEG power differences from 30 to 250 Hz between EO and EC across childhood. Developmental changes in EEG power showed spatial and frequency band differences as a function of age and EO/EC condition. A 64-electrode system was used to record EEG at 4, 5, 7, 9, and 11 years of age. Specific findings were: (1) the alpha peak shifts from 8 Hz at 4 years to 9 Hz at 11 years, (2) EC results in increased EEG power (compared to EO) at lower frequencies but decreased EEG power at higher frequencies for all ages, (3) the EEG power difference between EO and EC changes from positive to negative within a narrow frequency band which shifts toward higher frequencies with age, from 9 to 12 Hz at 4 years to 32 Hz at 11 years, (4) at all ages EC is characterized by an increase in lower frequency EEG power most prominently over posterior regions, (5) at all ages, during EC, decreases in EEG power above 30 Hz are mostly over anterior regions of the scalp. This report demonstrates that the simple challenge of opening and closing the eyes offers the potential to provide quantitative biomarkers of phenotypic variation in brain maturation by employing a brief, minimally invasive protocol throughout childhood.

Prenatal smoking and drinking are associated with altered newborn autonomic functions.

BACKGROUND: Prenatal smoking and drinking are associated with sudden infant death syndrome and neurodevelopmental disorders. Infants with these outcomes also have altered autonomic nervous system (ANS) regulation. We examined the effects of prenatal smoking and drinking on newborn ANS function. METHODS: Pregnant women were enrolled in Northern Plains, USA (NP) and Cape Town (CT), South Africa. Daily drinking and weekly smoking data were collected prenatally. Physiological measures were obtained during sleep 12-96 h post-delivery. RESULTS: In all, 2913 infants from NP and 4072 from CT were included. In active sleep, newborns of mothers who smoked throughout pregnancy, compared to non-smokers, had higher breathing rates (2.2 breaths/min; 95% CI: 0.95, 3.49). Quit-early smoking was associated with reductions in beat-to-beat heart rate variability (HRV) in active (-0.08 s) and quiet sleep (-0.11 s) in CT. In girls, moderate-high continuous smoking was associated with increased systolic (3.0 mmHg, CI: 0.70, 5.24) and diastolic blood pressure (2.9 mmHg, CI: 0.72, 5.02). In quiet sleep, low-continuous drinking was associated with slower heart rate (-4.5 beat/min). In boys, low-continuous drinking was associated with a reduced ratio of low-to-high frequency HRV (-0.11, CI: -0.21, -0.02). CONCLUSIONS: These findings highlight potential ANS pathways through which prenatal drinking and smoking may contribute to neurodevelopment outcomes. IMPACT: In this prospective cohort study of 6985 mother-infant dyads prenatal drinking and smoking were associated with multiple ANS parameters. Smoking was associated with increased neonatal breathing rates among all infants, and heart rate variability (HRV) and blood pressure (BP) among girls. Drinking was associated with reductions in HR and BP among all newborns, and reductions in the ratio of low to-high frequency HRV among boys. These findings suggest that prenatal smoking and drinking alter newborn ANS which may presage future neurodevelopmental disorders.

Pandemic beyond the virus: maternal COVID-related postnatal stress is associated with infant temperament.

BACKGROUND: Studies have shown that infant temperament varies with maternal psychosocial factors, in utero illness, and environmental stressors. We predicted that the pandemic would shape infant temperament through maternal SARS-CoV-2 infection during pregnancy and/or maternal postnatal stress. To test this, we examined associations among infant temperament, maternal prenatal SARS-CoV-2 infection, maternal postnatal stress, and postnatal COVID-related life disruptions. METHODS: We tested 63 mother-infant dyads with prenatal maternal SARS-CoV-2 infections and a comparable group of 110 dyads without infections. To assess postnatal maternal stress, mothers completed the Perceived Stress Scale 4 months postpartum and an evaluation of COVID-related stress and life disruptions 6 months postpartum. Mothers reported on infant temperament when infants were 6-months-old using the Infant Behavior Questionnaire-Revised (IBQ-R) Very Short Form. RESULTS: Maternal SARS-CoV-2 infection during pregnancy was not associated with infant temperament or maternal postnatal stress. Mothers with higher self-reported postnatal stress rated their infants lower on the Positive Affectivity/Surgency and Orienting/Regulation IBQ-R subscales. Mothers who reported greater COVID-related life disruptions rated their infants higher on the Negative Emotionality IBQ-R subscale. CONCLUSIONS: Despite no effect of prenatal maternal SARS-CoV-2 infection, stress and life disruptions incurred by the COVID-19 pandemic were associated with infant temperament at 6-months. IMPACT: SARS-CoV-2 infection during pregnancy is not associated with postnatal ratings of COVID-related life disruptions, maternal stress, or infant temperament. Postnatal ratings of maternal stress during the COVID-19 pandemic are associated with normative variation in maternal report of infant temperament at 6 months of age. Higher postnatal ratings of maternal stress are associated with lower scores on infant Positive Affectivity/Surgency and Orienting/Regulation at 6 months of age. Higher postnatal ratings of COVID-related life disruptions are associated with higher scores on infant Negative Emotionality at 6 months of age.

An automated heart rate-based algorithm for sleep stage classification: Validation using conventional polysomnography and an innovative wearable electrocardiogram device.

Background: The rapid advancement in wearable solutions to monitor and score sleep staging has enabled monitoring outside of the conventional clinical settings. However, most of the devices and algorithms lack extensive and independent validation, a fundamental step to ensure robustness, stability, and replicability of the results beyond the training and testing phases. These systems are thought not to be feasible and reliable alternatives to the gold standard, polysomnography (PSG). Materials and methods: This validation study highlights the accuracy and precision of the proposed heart rate (HR)-based deep-learning algorithm for sleep staging. The illustrated solution can perform classification at 2-levels (Wake; Sleep), 3-levels (Wake; NREM; REM) or 4- levels (Wake; Light; Deep; REM) in 30-s epochs. The algorithm was validated using an open-source dataset of PSG recordings (Physionet CinC dataset, n = 994 participants, 994 recordings) and a proprietary dataset of ECG recordings (Z3Pulse, n = 52 participants, 112 recordings) collected with a chest-worn, wireless sensor and simultaneous PSG collection using SOMNOtouch. Results: We evaluated the performance of the models in both datasets in terms of Accuracy (A), Cohen's kappa (K), Sensitivity (SE), Specificity (SP), Positive Predictive Value (PPV), and Negative Predicted Value (NPV). In the CinC dataset, the highest value of accuracy was achieved by the 2-levels model (0.8797), while the 3-levels model obtained the best value of K (0.6025). The 4-levels model obtained the lowest SE (0.3812) and the highest SP (0.9744) for the classification of Deep sleep segments. AHI and biological sex did not affect scoring, while a significant decrease of performance by age was reported across the models. In the Z3Pulse dataset, the highest value of accuracy was achieved by the 2-levels model (0.8812), whereas the 3-levels model obtained the best value of K (0.611). For classification of the sleep states, the lowest SE (0.6163) and the highest SP (0.9606) were obtained for the classification of Deep sleep segment. Conclusion: The results of the validation procedure demonstrated the feasibility of accurate HR-based sleep staging. The combination of the proposed sleep staging algorithm with an inexpensive HR device, provides a cost-effective and non-invasive solution deployable in the home environment and robust across age, sex, and AHI scores.

A Novel Method for the Extraction of Fetal ECG Signals from Wearable Devices.

The role of fetal surveillance for the prediction and timely assessment of fetal distress is widely established. Fetal ECG (fECG) monitoring via wearable devices is a feasible solution for performing continuous monitoring of fetal wellbeing and it has seen a net increase in popularity in recent years. In this paper, we propose a novel adaptation of the Smart AdaptiVe Ecg Recognition (SAVER) algorithm for the detection of fECG in long-duration recordings acquired in clinical as well as unconventional settings. The methodology was trained and tested on 50 recordings of duration 1 hour ( 59.33 ±5.54 min) obtained using the Monica AN24 fetal monitor. We validated the performance against the automatic extraction performed by the Monica DK software. Our results show superior reliability of the proposed methodology in extracting fECG and associated estimates of fetal heart rate (fHR). Clinical relevance- The proposed methodology provides an efficient and reliable approach for the extraction of fECG signals acquired via wearable technologies, enabling continuous monitoring of fECG in and outside clinical settings.

A Novel Method for ECG Artifact Removal from EEG without Simultaneous ECG.

The electrocardiogram (ECG) is a common source of electrical artifact in electroencephalogram (EEG). Here, we present a novel method for removing ECG artifact that requires neither simultaneous ECG nor transformation of the EEG signals. The approach relies upon processing a subset of EEG channels that contain ECG artifact to identify the times of each R-wave of the ECG. Within selected brief epochs, data in each EEG channel is signal-averaged ± 60 ms around each R-wave to derive an ECG template specific to each channel. This template is subtracted from each EEG channel which are aligned with the R-waves. The methodology was developed using two cohorts of infants: one with 128-lead EEG including an ECG reference and another with 32-lead EEG without ECG reference. The results for the first cohort validated the methodology the ECG reference and the second demonstrated its feasibility when ECG was not recorded. This method does not require independent, simultaneous recording of ECG, nor does it involve creation of an artifact template based on a mixture of EEG channel data as required by other methods such as Independent Component Analysis (ICA). Spectral analysis confirms that the method compares favorably to results using simultaneous recordings of ECG. The method removes ECG artifact on an epoch by epoch level and does not require stationarity of the artifact. Clinical Relevance - This approach facilitates the removal of ECG noise in frequency bands known to play a central role in brain mechanisms underlying cognitive processes.

Racial/ethnic disparities in infant sleep in the COVID-19 Mother Baby Outcomes (COMBO) study.

OBJECTIVE: Investigate racial and ethnic differences in infant sleep and examine associations with insurance status and parent-infant bedtime behavioral factors (PIBBF). METHODS: Participants are part of the COVID-19 Mother Baby Outcomes (COMBO) Initiative, Columbia University. Data on infant sleep (night, day and overall sleep duration, night awakenings, latency, infant's sleep as a problem) were collected at 4 months postpartum. Regressions estimated associations between race/ethnicity, insurance status, PIBBF and infants' sleep. RESULTS: A total of 296 infants were eligible (34.4% non-Hispanic White [NHW], 10.1% Black/African American [B/AA], 55.4% Hispanic). B/AA and Hispanic mothers were more likely to have Medicaid, bed/room-share, and report later infant bedtime compared to NHW mothers. Infants of B/AA mothers had longer sleep latency compared to NHW. Infants of Hispanic mothers slept less at night (∼70 ± 12 minutes) and more during the day (∼41 ± 12 minutes) and Hispanic mothers were less likely to consider infants' sleep as a problem compared to NHW (odds ratio 0.4; 95% confidence interval: 0.2-0.7). After adjustment for insurance status and PIBBF, differences by race/ethnicity for night and day sleep duration and perception of infant's sleep as a problem persisted (∼32 ± 14 minutes, 35 ± 15 minutes, and odds ratio 0.4; 95% confidence interval: 0.2-0.8 respectively). Later bedtime was associated with less sleep at night (∼21 ± 4 minutes) and overall (∼17 ± 5 minutes), and longer latency. Infants who did not fall asleep independently had longer sleep latency, and co-sleeping infants had more night awakenings. CONCLUSIONS: Results show racial/ethnic differences in sleep in 4-month-old infants across sleep domains. The findings of our study suggest that PIBBF have an essential role in healthy infant sleep, but they may not be equitably experienced across racial/ethnic groups.

Aperiodic electrophysiological activity in preterm infants is linked to subsequent autism risk.

Approximately 7% of preterm infants receive an autism spectrum disorder (ASD) diagnosis. Yet, there is a significant gap in the literature in identifying prospective markers of neurodevelopmental risk in preterm infants. The present study examined two electroencephalography (EEG) parameters during infancy, absolute EEG power and aperiodic activity of the power spectral density (PSD) slope, in association with subsequent autism risk and cognitive ability in a diverse cohort of children born preterm in South Africa. Participants were 71 preterm infants born between 25 and 36 weeks gestation (34.60 ± 2.34 weeks). EEG was collected during sleep between 39 and 41 weeks postmenstrual age adjusted (40.00 ± 0.42 weeks). The Bayley Scales of Infant Development and Brief Infant Toddler Social Emotional Assessment (BITSEA) were administered at approximately 3 years of age adjusted (34 ± 2.7 months). Aperiodic activity, but not the rhythmic oscillatory activity, at multiple electrode sites was associated with subsequent increased autism risk on the BITSEA at three years of age. No associations were found between the PSD slope or absolute EEG power and cognitive development. Our findings highlight the need to examine potential markers of subsequent autism risk in high-risk populations other than infants at familial risk.