Figure 1 - uploaded by Madeleine Grigg-Damberger
Content may be subject to copyright.
Source publication
Unlabelled:
In March 2014, the American Academy of Sleep Medicine (AASM) Board of Directors requested the Scoring Manual Editorial Board develop rules, terminology, and technical specifications for scoring sleep/wake states in full-term infants from birth to 2 mo of age, cognizant of the 1971 Anders, Emde, and Parmelee Manual for Scoring Sleep in...
Context in source publication
Context 1
... during AS/REM sleep, REMs, small movements of the limbs or face, irregular respiration and heart rates, and no chin muscle activity were noted. They identified and named four different EEG patterns seen in term infants when sleeping: tracé alternant (TA), high voltage slow (HVS), activité moyenne (mixed, M), and low voltage irregular (LVI) 15,[26][27][28] (Figure 1). They recognized that normal infants had many periods (or epochs) of sleep that were not easily categorized as a particular sleep state because of discordant features between the physiological markers of sleep/wake states (EEG, EOG, chin EMG, respiration, and body move- ments). ...
Similar publications
Understanding human sleep requires appropriate animal models. Sleep has been extensively studied in rodents, although rodent sleep differs substantially from human sleep. Here we investigate sleep in tree shrews, small diurnal mammals phylogenetically close to primates, and compare it to sleep in rats and humans using electrophysiological recording...
Spectral analysis of neonatal sleep is useful for studying brain maturation; however, most studies have analyzed convS†FM_Abstract_Para_FlushLeftentional broad bands described for awake adults, so a distinct approach for EEG analysis may disclose new findings.
STUDY OBJECTIVES
To extract independent EEG broad bands using principal component analys...
Human High-Frequency-Oscillations (HFO) in the ripple band are oscillatory brain activity in the frequency range between 80 and 250 Hz. HFOs may comprise different subgroups that either play a role in physiologic or pathologic brain functions. An exact differentiation between physiologic and pathologic HFOs would help elucidate their relevance for...
Study objectives:
To assess the validity of sleep architecture and sleep continuity biomarkers obtained from a portable, multichannel forehead electroencephalography (EEG) recorder.
Methods:
Forty-seven subjects simultaneously underwent polysomnography (PSG) while wearing a multichannel frontopolar EEG recording device (Sleep Profiler). The PSG...
There is a growing interest in the application of psychophysiological signals in more applied settings. Unidirectional sensory motor rhythm-training (SMR) has demonstrated consistent effects on sleep. In this study the main aim was to analyze to what extent participants could gain voluntary control over sleep-related parameters and secondarily to a...
Citations
... All PSGs were reviewed and reported by a paediatric sleep physician using the scoring guidelines of American Academy of Sleep Medicine (AASM) Manual for the Scoring of Sleep and Associated Events. [15][16][17] Based on previous studies, severity of SDB was classified using the total apnoea-hypopnoea index (AHI): an AHI of <5 was considered normal, AHI of 5 to 9.9 mild, AHI of 10 to 14.9 moderate and AHI of 15.0 or higher was considered severe SDB. 6 12 PSG data related to CSA were also collected and reported. ...
Objective
Awareness of the need for early identification and treatment of sleep disordered breathing (SDB) in neonates is increasing but is challenging. Unrecognised SDB can have negative neurodevelopmental consequences. Our study aims to describe the clinical profile, risk factors, diagnostic modalities and interventions that can be used to manage neonates with SDB to facilitate early recognition and improved management.
Methods
A single-centre retrospective study of neonates referred for assessment of suspected SDB to a tertiary newborn intensive care unit in New South Wales Australia over a 2-year period. Electronic records were reviewed. Outcome measures included demographic data, clinical characteristics, comorbidities, reason for referral, polysomnography (PSG) data, interventions targeted to treat SDB and hospital outcome. Descriptive analysis was performed and reported.
Results
Eighty neonates were included. Increased work of breathing, or apnoea with oxygen desaturation being the most common reasons (46% and 31%, respectively) for referral. Most neonates had significant comorbidities requiring involvement of multiple specialists (mean 3.3) in management. The majority had moderate to severe SDB based on PSG parameters of very high mean apnoea-hypopnoea index (62.5/hour) with a mean obstructive apnoea index (38.7/hour). Ten per cent of patients required airway surgery. The majority of neonates (70%) were discharged home on non-invasive ventilation.
Conclusion
SDB is a serious problem in high-risk neonates and it is associated with significant multisystem comorbidities necessitating a multidisciplinary team approach to optimise management. This study shows that PSG is useful in neonates to diagnose and guide management of SDB.
... In contrast to active sleep, this state lasts longer (up to 60-90 min), has no rapid eye movements, and the breathing and heart rates of the newborns become more regular. Overall it is a preferable state for EEG recording, as the appearance of artifacts is much less likely [40][41][42] . In total, the experiment lasted approximately 30 min and consisted of 400 trials, with 100 trials per condition (as only the passive condition was considered, in contrast to the adult experiment). ...
Adaptive biases in favor of approaching, or “looming”, sounds have been found across ages and species, thereby implicating the potential of their evolutionary origin and universal basis. The human auditory system is well-developed at birth, yet spatial hearing abilities further develop with age. To disentangle the speculated inborn, evolutionary component of the auditory looming bias from its learned counterpart, we collected high-density electroencephalographic data across human adults and newborns. As distance-motion cues we manipulated either the sound’s intensity or spectral shape, which is pinna-induced and thus prenatally inaccessible. Through cortical source localisation we demonstrated the emergence of the bias in both age groups at the level of Heschl’s gyrus. Adults exhibited the bias in both attentive and inattentive states; yet differences in amplitude and latency appeared based on attention and cue type. Contrary to the adults, in newborns the bias was elicited only through manipulations of intensity and not spectral cues. We conclude that the looming bias comprises innate components while flexibly incorporating the spatial cues acquired through lifelong exposure.
... OSA was defined by an obstructive apnea-hypopnea index (OAHI) ≥ 2/h, moderate to severe OSA by an AHI > 5/h [10]. Sleep stages were categorized as R [equivalent to rapid eye movement (REM) sleep] or N (equivalent to NREM sleep) for infants under 2 months at the time of the polysomnography as recommended [11]. ...
Purpose
This study aimed to investigate the role of nap polysomnography (NPSG) in predicting treatment strategies for infants with moderate to severe laryngomalacia and to explore the association between obstructive sleep apnea (OSA) severity, weight gain, and laryngomalacia severity.
Methods
A retrospective analysis was conducted on infants diagnosed with moderate to severe laryngomalacia who underwent NPSG between January 2019 and June 2023. Clinical variables, NPSG parameters, and treatment decisions were collected. Weight gain rate and its correlation with NPSG indices were assessed. Logistic regression analyses were performed to predict treatment strategies based on NPSG findings.
Results
Of the 39 infants included (median age: 3.3 months), 77% exhibited OSA, with 69% having moderate to severe OSA [apnea–hypopnea index (AHI) > 5/h]. Weight gain rate correlated negatively with indices of OSA severity, including the hypopnea index (HI) and the AHI. In a multiple logistic regression analysis incorporating the severity of OSA (AHI), weight gain rate, and laryngomalacia severity, only AHI predicted the decision for surgical or non-invasive ventilation treatment (OR = 2.1, CI95 [1.6; 2.8], p ≤ 10–4). The weight gain rate was predicted (r² = 0.28) by the AHI and the presence of retractions of auxiliary inspiratory muscles.
Conclusion
This study underscores the importance of NPSG in assessing infants with moderate to severe laryngomalacia. The AHI from NPSG emerged as a potential predictor for treatment decisions and weight gain rate, emphasizing its clinical relevance. These findings advocate incorporating NPSG into the diagnostic and management process for infants with laryngomalacia.
... Sleep for mother/parent/baby [13,[20][21][22] • Time in sleep • Sleep assessment [23] Breastfeeding/Mother's own milk (MOM) ...
... Time in sleep can be recorded for mother, baby, and father/partner. The quality of the baby's sleep can be assessed using a visual scoring of sleep [23]. ...
Objective
The evidence-based science of maternal and neonatal care has been rapidly changing. As a result, clinical practice and the design of physical space have evolved in order to provide neuroprotection for the baby and meet expectations of family presence and participation.
Setting
The concept and practice of NICU Couplet Care supports positive health well-being/outcomes and early relationship building between the mother-baby-father/partner.
Results
Monitoring evidence-based measures and metrics of standardized care, performance competence, neuro-physical and psychosocial outcomes, environmental design, family and staff satisfaction, and sustainability are essential to the evolution of quality, safe, efficient, effective, ethical, and cost-effective care for the mother, baby, and family.
Summary
Transparency in the dissemination of evidence, practice standards, and outcome data is important to guide parents/families and health professionals in making informed shared decisions regarding the clinical care provided and the environment where care takes place.
... Interestingly, light stimulation reduced active sleep during the day and quiet sleep during the night. This reason for the daytime decrease in active sleep is unclear, but one possible explanation could be related to the fact that early infants enter the sleep cycle starting with active sleep, in contrast to adults, who enter with non-REM sleep [1,31]. Because active sleep is not deep, infants wake easily in daytime lighted environments, and this may result in a decrease in active sleep during the daytime. ...
... Cerebral tissue oxygenation index (TOI, %) was measured using Near Infrared Spectroscopy (NIRO 200, Hamamatsu Photonics K.K., Hamamatsu City, Japan) [10,17,18]. Sleep state was scored in real time as active sleep (AS), indeterminate sleep (IS) or quiet sleep (QS) using established bedside behavioral criteria [19]. ...
Objective
We investigated the relationship between respiratory events experienced before and after hospital discharge and developmental outcomes at 6 months corrected age (CA).
Study design
Preterm infants born between 28–32 weeks gestational age (GA) were studied at 32–36 weeks postmenstrual age (PMA), 36–40 weeks PMA, 3- and 6-months CA. Percentage total sleep time (%TST) with respiratory events (isolated apneas, sequential apneas and periodic breathing (PB)) at each study was calculated. Stepwise multiple linear regressions determined significant predictors of developmental outcomes at 6 months.
Result
%TST with respiratory events at term were significant predictors of language (R² = 0.165, β = −0.416) and motor (R² = 0.180, β = −0.485) composite scores of the Bayley Scales of Infant Development at 6 months, independent of GA, birth weight and sex.
Conclusions
In clinically stable very preterm infants at term equivalent age, time spent having respiratory events, was related to a reduction in language and motor outcomes at 6 months.
... Early manifestations of sleep-wake cycling can be observed in electroencephalography (EEG) around 27 weeks postmenstrual age (PMA), and then developed into distinct electrophysiological patterns, which can be observed on the signals recorded by video EEG or polysomnography (PSG). After 28 weeks PMA, neonatal sleep can generally be divided into active sleep (AS), quiet sleep (QS), and wake stage [7]- [9]. Meanwhile, at the onset of term-age, normally after 36 weeks PMA, AS and QS can be further divided into AS I, AS II, and QS I, QS II, respectively. ...
... In this paper, a total of eight monopolar EEG channels located at F3, F4, C3, C4, T3, T4, P3, and P4 sites according to the International 10-20 System were attached. The experimental protocol of the electrode placement incorporates the American Academy of Sleep Medicine (AASM) manual for infant scoring criteria [9] and clinical demands. On the basis of these eight channels, the impact of channel reduction is investigated. ...
Most existing neonatal sleep staging approaches applied multiple EEG channels to obtain good performance. However, it potentially increased the computational complexity and led to an increased risk of skin disruption to neonates during data acquisition. In this paper, a multi-scale hierarchical neural network (MS-HNN) with a squeeze and excitation (SE) block for neonatal sleep staging is presented in this study on the basis of a single EEG channel. MS-HNN composes of multi-scale convolutional neural network (MSCNN), temporal information learning (TIL) module, and squeeze and excitation (SE) block. MSCNN can extract features from different scales and frequencies, and TIL module can acquire the transition information among adjacent stages. In addition, for these extracted features, SE block can selectively concentrate on informative features and weaken redundant features for achieving better performance. The proposed approach was validated on a clinical dataset involving 64 neonates from the Children's Hospital of Fudan University (CHFU). The proposed network achieves an accuracy of 75.4% and 76.5% for three-class automatic neonatal sleep staging with the single-EEG channel and the eight-EEG channels, respectively. The experimental results show that the proposed method can maintain good performance by making full use of the information in the single channel while reducing the channels to control the computational overhead.
... While this study provides insight to the benefits of amplification for early perceptual development in IHH, there are several limitations that should be considered when interpreting these results. Time is limited to the average sleep cycle in young infants, approximately 50-60 min [54], which limits the number of stimuli we can present in a single EEG session. Our preference would have been to record two different auditory contrasts (i.e.,/ba-da/and/PPT-BBN/) within the same group of infants in both the aided and unaided condition. ...
Our objective was to examine the effects of hearing aid amplification on auditory detection and discrimination in infants who were hard of hearing (IHH) using a physiological measure of auditory perception. We recorded EEG from 41 sleeping IHH aged 1.04 to 5.62 months while presenting auditory stimuli in a mismatch response paradigm. Responses were recorded during two listening conditions for each participant: aided and unaided. Temporal envelopes of the mismatch response in the EEG alpha band (6–12 Hz) were extracted from the latent, time-frequency transformed data. Aided alpha band responses were greater than unaided responses for the deviant trials but were not different for the standard trials. Responses to the deviant trials were greater than responses to the standard trials for the aided conditions but were not different for the unaided conditions. These results suggest that the alpha band mismatch can be used to examine both detection and discrimination of speech and non-speech sounds in IHH. With further study, the alpha band mismatch could expand and refine our abilities to validate hearing aid fittings at younger ages than current clinical protocols allow.
... This is an interesting finding since small children exhibit more REM sleep (see Supplementary Fig. 11). Visual scoring guidelines for small children differ from the guidelines for adults, with REM sleep scoring strongly relying on irregular respiration 44 . However, overall these results show that, despite the age-related differences, the DL algorithm is able to deal with different age subgroups at the same time, without needing to have access to chronological age-related information during the training procedure. ...
AASM guidelines are the result of decades of efforts aiming at standardizing sleep scoring procedure, with the final goal of sharing a worldwide common methodology. The guidelines cover several aspects from the technical/digital specifications, e.g., recommended EEG derivations, to detailed sleep scoring rules accordingly to age. Automated sleep scoring systems have always largely exploited the standards as fundamental guidelines. In this context, deep learning has demonstrated better performance compared to classical machine learning. Our present work shows that a deep learning-based sleep scoring algorithm may not need to fully exploit the clinical knowledge or to strictly adhere to the AASM guidelines. Specifically, we demonstrate that U-Sleep, a state-of-the-art sleep scoring algorithm, can be strong enough to solve the scoring task even using clinically non-recommended or non-conventional derivations, and with no need to exploit information about the chronological age of the subjects. We finally strengthen a well-known finding that using data from multiple data centers always results in a better performing model compared with training on a single cohort. Indeed, we show that this latter statement is still valid even by increasing the size and the heterogeneity of the single data cohort. In all our experiments we used 28528 polysomnography studies from 13 different clinical studies.
... EEG activity describes background continuity (continuous or discontinuous), frequency of activity, and amplitude or voltage (µV) of activity, with associated alterations in behaviour and cardiorespiratory parameters (Table 1). [11][12][13] Frequency of activity measured in Hertz (Hz) includes delta (0.5-4 Hz), theta (4)(5)(6)(7)(8), alpha (8)(9)(10)(11)(12) and beta activity. Amplitude is described as either high (>50 µV), medium (between 50 and 25 µV) or low amplitude, which for the purposes of this manuscript we have identified as <25 µV. ...
... EEG activity describes background continuity (continuous or discontinuous), frequency of activity, and amplitude or voltage (µV) of activity, with associated alterations in behaviour and cardiorespiratory parameters (Table 1). [11][12][13] Frequency of activity measured in Hertz (Hz) includes delta (0.5-4 Hz), theta (4)(5)(6)(7)(8), alpha (8)(9)(10)(11)(12) and beta activity. Amplitude is described as either high (>50 µV), medium (between 50 and 25 µV) or low amplitude, which for the purposes of this manuscript we have identified as <25 µV. ...
... 21,22 All recordings adhered to a standard modified neonatal version of the international 10/20 system that ensured consistency in the positioning of EEG electrodes. 12 Scalp electrode sites were prepared by cleaning with Nuprep gel and eleven sterile disposable hydrogel electrodes were applied with additional water-soluble conductive paste. Electrode placement positions were at F3, F4, C3, C4, Cz, T3, T4, O1, O2, plus a reference electrode on the frontal region of the head (R) and ground electrode (G) placed behind the left ear. ...
Background
Sleep supports neurodevelopment and sleep architecture reflects brain maturation. This prospective observational study describes the nocturnal sleep architecture of healthy moderate to late preterm (MLP) infants in the neonatal unit at 36 weeks post menstrual age (PMA).
Methods
MLP infants, in the neonatal unit of a tertiary hospital in Ireland from 2017 to 2018, had overnight continuous electroencephalography (cEEG) with video for a minimum 12 h at 36 weeks PMA. The total sleep time (TST) including periods of active sleep (AS), quiet sleep (QS), indeterminate sleep (IS), wakefulness and feeding were identified, annotated and quantified.
Results
A total of 98 infants had cEEG with video monitoring suitable for analysis. The median (IQR) of TST in the 12 h period was 7.09 h (IQR 6.61–7.76 h), 4.58 h (3.69–5.09 h) in AS, 2.02 h (1.76–2.36 h) in QS and 0.65 h (0.48–0.89 h) in IS. The total duration of AS was significantly lower in infants born at lower GA ( p = 0.007) whilst the duration of individual QS periods was significantly higher ( p = 0.001).
Conclusion
Overnight cEEG with video at 36 weeks PMA showed that sleep state architecture is dependent on birth GA. Infants with a lower birth GA have less AS and more QS that may have implications for later neurodevelopment.
Impact
EEG provides objective information about the sleep organisation of the moderate to late preterm (MLP) infant.
Quantitative changes in sleep states occur with each week of advancing gestational age (GA).
Active sleep (AS) is the dominant sleep state that was significantly lower in infants born at lower GA.
MLP infants who were exclusively fed orally had a shorter total sleep time and less AS compared to infants who were fed via nasogastric tube.
