[HTML][HTML] Automated sleep stage classification in sleep apnoea using convolutional neural networks
GN Sundar, D Narmadha, AAA Jone… - Informatics in Medicine …, 2021 - Elsevier
A sleep disorder is a condition that adversely impacts one's ability to sleep well on a regular
schedule. It also occurs as a consequence of numerous neurological sicknesses. These …
schedule. It also occurs as a consequence of numerous neurological sicknesses. These …
Attention based convolutional network for automatic sleep stage classification
S Sun, C Li, N Lv, X Zhang, Z Yu… - Biomedical Engineering …, 2021 - degruyter.com
Sleep staging is an important basis for diagnosing sleep-related problems. In this paper, an
attention based convolutional network for automatic sleep staging is proposed. The network …
attention based convolutional network for automatic sleep staging is proposed. The network …
A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time series
S Chambon, MN Galtier, PJ Arnal… - … on Neural Systems …, 2018 - ieeexplore.ieee.org
Sleep stage classification constitutes an important preliminary exam in the diagnosis of
sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of …
sleep disorders. It is traditionally performed by a sleep expert who assigns to each 30 s of …
Accurate deep learning-based sleep staging in a clinical population with suspected obstructive sleep apnea
The identification of sleep stages is essential in the diagnostics of sleep disorders, among
which obstructive sleep apnea (OSA) is one of the most prevalent. However, manual scoring …
which obstructive sleep apnea (OSA) is one of the most prevalent. However, manual scoring …
A deep learning approach with an attention mechanism for automatic sleep stage classification
M Längkvist, A Loutfi - arXiv preprint arXiv:1805.05036, 2018 - arxiv.org
Automatic sleep staging is a challenging problem and state-of-the-art algorithms have not
yet reached satisfactory performance to be used instead of manual scoring by a sleep …
yet reached satisfactory performance to be used instead of manual scoring by a sleep …
Multichannel sleep stage classification and transfer learning using convolutional neural networks
Current sleep medicine relies on the supervised analysis of polysomnographic
measurements, comprising amongst others electroencephalogram (EEG), electromyogram …
measurements, comprising amongst others electroencephalogram (EEG), electromyogram …
Automatic sleep stage classification: From classical machine learning methods to deep learning
RN Sekkal, F Bereksi-Reguig… - … Signal Processing and …, 2022 - Elsevier
Background and objectives The classification of sleep stages is a preliminary exam that
contributes to the diagnosis of possible sleep disorders. However, it is a tedious and time …
contributes to the diagnosis of possible sleep disorders. However, it is a tedious and time …
A compact deep learning network for temporal sleep stage classification
A Vetek, K Müller, H Lindholm - 2018 IEEE life sciences …, 2018 - ieeexplore.ieee.org
Sleep stage classification is usually performed by trained professionals using visual
inspection of bio-electrical recordings from a subject and is the first step in quantifying the …
inspection of bio-electrical recordings from a subject and is the first step in quantifying the …
Automated detection of sleep stages using deep learning techniques: A systematic review of the last decade (2010–2020)
Sleep is vital for one's general well-being, but it is often neglected, which has led to an
increase in sleep disorders worldwide. Indicators of sleep disorders, such as sleep …
increase in sleep disorders worldwide. Indicators of sleep disorders, such as sleep …
Deep learning application to clinical decision support system in sleep stage classification
Recently, deep learning for automated sleep stage classification has been introduced with
promising results. However, as many challenges impede their routine application, automatic …
promising results. However, as many challenges impede their routine application, automatic …