Hybrid spiking neural network for sleep electroencephalogram signals
Sleep staging is important for assessing sleep quality. So far, many scholars have tried to
achieve automatic sleep staging by using neural networks. However, most researchers only …
achieve automatic sleep staging by using neural networks. However, most researchers only …
Deep learning in EEG: Advance of the last ten-year critical period
Deep learning has achieved excellent performance in a wide range of domains, especially
in speech recognition and computer vision. Relatively less work has been done for …
in speech recognition and computer vision. Relatively less work has been done for …
[HTML][HTML] Sleep stage classification in children using self-attention and Gaussian noise data augmentation
The analysis of sleep stages for children plays an important role in early diagnosis and
treatment. This paper introduces our sleep stage classification method addressing the …
treatment. This paper introduces our sleep stage classification method addressing the …
A comprehensive evaluation of contemporary methods used for automatic sleep staging
D Sarkar, D Guha, P Tarafdar, S Sarkar… - … Signal Processing and …, 2022 - Elsevier
This paper presents a systematic review of automatic sleep staging studies.
Polysomnographic (PSG) data is used for the study of sleep staging. The benchmark for …
Polysomnographic (PSG) data is used for the study of sleep staging. The benchmark for …
Automatic sleep staging based on a hybrid stacked LSTM neural network: verification using large-scale dataset
CE Kuo, GT Chen - IEEE access, 2020 - ieeexplore.ieee.org
Previously reported automatic sleep staging methods have usually been developed using
healthy groups of fewer than 100 subjects. In this study, an automatic sleep staging method …
healthy groups of fewer than 100 subjects. In this study, an automatic sleep staging method …
Neonatal sleep stage identification using long short-term memory learning system
L Fraiwan, M Alkhodari - Medical & Biological Engineering & Computing, 2020 - Springer
Neonatal sleep analysis at the neonatal intensive care units (NICU) is critical for the
diagnosis of any brain growth risks during the early stages of life. In this paper, an …
diagnosis of any brain growth risks during the early stages of life. In this paper, an …
[HTML][HTML] Deep learning-based algorithm accurately classifies sleep stages in preadolescent children with sleep-disordered breathing symptoms and age-matched …
Introduction Visual sleep scoring has several shortcomings, including inter-scorer
inconsistency, which may adversely affect diagnostic decision-making. Although automatic …
inconsistency, which may adversely affect diagnostic decision-making. Although automatic …
A compressive sensing-based automatic sleep-stage classification system with radial basis function neural network
This study presents an automatic sleep-stage classification system based on utilizing
compressive sensing (CS) for data reduction. The amount of electroencephalogram (EEG) …
compressive sensing (CS) for data reduction. The amount of electroencephalogram (EEG) …
Pediatric automatic sleep staging: a comparative study of state-of-the-art deep learning methods
Background: Despite the tremendous prog-ress recently made towards automatic sleep
staging in adults, it is currently unknown if the most advanced algorithms generalize to the …
staging in adults, it is currently unknown if the most advanced algorithms generalize to the …
Time-frequency deep metric learning for multivariate time series classification
Z Chen, Y Liu, J Zhu, Y Zhang, R Jin, X He, J Tao… - Neurocomputing, 2021 - Elsevier
Multivariate time series (MTS) data exist in various fields of studies and MTS classification is
an important research topic in the machine learning community. Researchers have …
an important research topic in the machine learning community. Researchers have …