Single-Channel EEG Data Analysis Using a Multi-Branch CNN for Neonatal Sleep Staging
HA Siddiqa, Z Tang, Y Xu, L Wang, M Irfan… - IEEE …, 2024 - ieeexplore.ieee.org
Neonatal sleep staging is crucial for understanding infant brain development and assessing
neurological health. This study explores the optimal electrode configuration to reduce …
neurological health. This study explores the optimal electrode configuration to reduce …
EEG-based neonatal sleep-wake classification using multilayer perceptron neural network
Objective: Classification of sleep-wake states using multichannel electroencephalography
(EEG) data that reliably work for neonates. Methods: A deep multilayer perceptron (MLP) …
(EEG) data that reliably work for neonates. Methods: A deep multilayer perceptron (MLP) …
[PDF][PDF] Electroencephalography (EEG) Based Neonatal Sleep Staging and Detection Using Various Classification Algorithms
Automatic sleep staging of neonates is essential for monitoring their brain development and
maturity of the nervous system. EEG based neonatal sleep staging provides valuable …
maturity of the nervous system. EEG based neonatal sleep staging provides valuable …
MS-HNN: Multi-scale hierarchical neural network with squeeze and excitation block for neonatal sleep staging using a single-channel EEG
Most existing neonatal sleep staging appro-aches applied multiple EEG channels to obtain
good performance. However, it potentially increased the computational complexity and led …
good performance. However, it potentially increased the computational complexity and led …
Neonatal EEG sleep stage classification based on deep learning and HMM
Objective. Automatic sleep stage scoring is of great importance for investigating sleep
architecture during infancy. In this work, we introduce a novel multichannel approach based …
architecture during infancy. In this work, we introduce a novel multichannel approach based …
Development of Sleep State Trend (SST), a bedside measure of neonatal sleep state fluctuations based on single EEG channels
SM Moghadam, P Nevalainen, NJ Stevenson… - arXiv preprint arXiv …, 2022 - arxiv.org
Objective: To develop and validate an automated method for bedside monitoring of sleep
state fluctuations in neonatal intensive care units. Methods: A deep learning-based …
state fluctuations in neonatal intensive care units. Methods: A deep learning-based …
A Sequential End-to-End Neonatal Sleep Staging Model with Squeeze and Excitation Blocks and Sequential Multi-Scale Convolution Neural Networks.
Automatic sleep staging offers a quick and objective assessment for quantitatively
interpreting sleep stages in neonates. However, most of the existing studies either do not …
interpreting sleep stages in neonates. However, most of the existing studies either do not …
[HTML][HTML] Feasibility of automated early postnatal sleep staging in extremely and very preterm neonates using dual-channel EEG
X Wang, A Bik, ER de Groot, ML Tataranno… - Clinical …, 2023 - Elsevier
Objective To investigate the feasibility of automated sleep staging based on quantitative
analysis of dual-channel electroencephalography (EEG) for extremely and very preterm …
analysis of dual-channel electroencephalography (EEG) for extremely and very preterm …
Pediatric sleep stage classification using multi-domain hybrid neural networks
Sleep staging is an important part of clinical neurology. However, it is still performed
manually by technical experts and is labor-intensive and time-consuming. To overcome …
manually by technical experts and is labor-intensive and time-consuming. To overcome …
A convolutional neural network outperforming state-of-the-art sleep staging algorithms for both preterm and term infants
Objective. To classify sleep states using electroencephalogram (EEG) that reliably works
over a wide range of preterm ages, as well as term age. Approach. A convolutional neural …
over a wide range of preterm ages, as well as term age. Approach. A convolutional neural …