Inter-limb time-varying singular value: A new gait feature for Parkinson’s disease detection and stage classification
Sign Up to like & getrecommendations! Published in 2021 at "Measurement"
DOI: 10.1016/j.measurement.2021.109249
Abstract: Abstract The development of a reliable but cost-effective Parkinson’s disease (PD) detection and severity stage classification system is one of the important aspects of medical application. Hence, this paper has provided a new cost-effective approach… read more here.
Keywords: stage classification; singular value; detection;
Automatic sleep stage classification based on a two-channel electrooculogram and one-channel electromyogram
Sign Up to like & getrecommendations! Published in 2022 at "Physiological Measurement"
DOI: 10.1088/1361-6579/ac6bdb
Abstract: Objective. Sleep monitoring by polysomnography (PSG) severely degrades sleep quality. In order to reduce the load of sleep monitoring, an approach to automatic sleep stage classification without an electroencephalogram (EEG) was proposed. Approach. A total… read more here.
Keywords: stage classification; sleep stage; automatic sleep; sleep ... See more keywords
MRASleepNet: a multi-resolution attention network for sleep stage classification using single-channel EEG
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/aca2de
Abstract: Objective. Computerized classification of sleep stages based on single-lead electroencephalography (EEG) signals is important, but still challenging. In this paper, we proposed a deep neural network called MRASleepNet for automatic sleep stage classification using single-channel… read more here.
Keywords: classification; sleep stage; model; stage classification ... See more keywords
A Two-Stage Learning Convolutional Neural Network for Sleep Stage Classification Using a Filterbank and Single Feature
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3180730
Abstract: Sleep is an essential process for the body that helps to maintain its health and vitality. The first stage in the diagnosis and treatment of sleep disorders is sleep staging. Due to the complications in… read more here.
Keywords: sleep staging; classification; sleep stage; single feature ... See more keywords
Automatic Sleep Stage Classification Using Deep Learning Algorithm for Multi-Institutional Database
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3275087
Abstract: Recent deep learning studies for sleep stage classification with polysomnography (PSG) data show two directions, either using 1-dimensional (1-D) raw PSG data or spectrogram images time-frequency domain. We propose a novel approach using images generated… read more here.
Keywords: classification; sleep stage; class; deep learning ... See more keywords
MVF-SleepNet: Multi-View Fusion Network for Sleep Stage Classification.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2022.3208314
Abstract: Sleep stage classification is of great importance in human health monitoring and disease diagnosing. Clinically, visual-inspected classifying sleep into different stages is quite time consuming and highly relies on the expertise of sleep specialists. Many… read more here.
Keywords: stage classification; sleep stage; mvf sleepnet;
CoSleep: A Multi-View Representation Learning Framework for Self-Supervised Learning of Sleep Stage Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2021.3130826
Abstract: Sleep stage classification is critical for diagnosing sleep quality. While deep neural networks are becoming popular for automatic sleep stage classification with supervised learning, large-scale labeled datasets are still hard to acquire. Recently, self-supervised learning… read more here.
Keywords: stage classification; sleep stage; self supervised; supervised learning ... See more keywords
Automatic Sleep Stage Classification Based on Subthalamic Local Field Potentials
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2018.2890272
Abstract: Deep brain stimulation (DBS) is an established treatment for patients with Parkinson’s disease (PD). Sleep disorders are common complications of PD and affected by subthalamic DBS treatment. To achieve more precise neuromodulation, chronicsleepmonitoringand closed-loop DBS… read more here.
Keywords: stage classification; local field; classification; sleep stage ... See more keywords
SleepFCN: A Fully Convolutional Deep Learning Framework for Sleep Stage Classification Using Single-Channel Electroencephalograms
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2022.3192988
Abstract: Sleep is a vital process of our daily life as we roughly spend one-third of our lives asleep. In order to evaluate sleep quality and potential sleep disorders, sleep stage classification is a gold standard… read more here.
Keywords: using single; classification; sleep stage; stage classification ... See more keywords
Self-Supervised Learning for Label- Efficient Sleep Stage Classification: A Comprehensive Evaluation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2023.3245285
Abstract: The past few years have witnessed a remarkable advance in deep learning for EEG-based sleep stage classification (SSC). However, the success of these models is attributed to possessing a massive amount of labeled data for… read more here.
Keywords: self supervised; sleep stage; supervised learning; stage classification ... See more keywords
A Comparison Study on Multidomain EEG Features for Sleep Stage Classification
Sign Up to like & getrecommendations! Published in 2017 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2017/4574079
Abstract: Feature extraction from physiological signals of EEG (electroencephalogram) is an essential part for sleep staging. In this study, multidomain feature extraction was investigated based on time domain analysis, nonlinear analysis, and frequency domain analysis. Unlike… read more here.
Keywords: sleep stage; time domain; stage classification; study multidomain ... See more keywords