Výsledky vyhledávání - "Cooray, Navin"

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Automated Movement Detection with Dirichlet Process Mixture Models and Electromyography

Autor: Cooray, Navin, Li, Zhenglin, Wang, Jinzhuo, Lo, Christine, Arvaneh, Mahnaz, Symmonds, Mkael, Hu, Michele, De Vos, Maarten, Mihaylova, Lyudmila S

Publikováno v: 2022 25th International Conference on Information Fusion (FUSION), Link\"oping, Sweden, 2022, pp. 01-08

Numerous sleep disorders are characterised by movement during sleep, these include rapid-eye movement sleep behaviour disorder (RBD) and periodic limb movement disorder. The process of diagnosing movement related sleep disorders requires laborious an

Externí odkaz: http://arxiv.org/abs/2302.07509

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Screening for REM Sleep Behaviour Disorder with Minimal Sensors

Autor: Cooray, Navin, Andreotti, Fernando, Lo, Christine, Symmonds, Mkael, Hu, Michele T. M., De Vos, Maarten

Rapid-Eye-Movement (REM) sleep behaviour disorder (RBD) is an early predictor of Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. This study investigates a minimal set of sensors to achieve effective screening for RBD in t

Externí odkaz: http://arxiv.org/abs/1910.11702

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Detection of REM Sleep Behaviour Disorder by Automated Polysomnography Analysis

Autor: Cooray, Navin, Andreotti, Fernando, Lo, Christine, Symmonds, Mkael, Hu, Michele T. M., De Vos, Maarten

Evidence suggests Rapid-Eye-Movement (REM) Sleep Behaviour Disorder (RBD) is an early predictor of Parkinson's disease. This study proposes a fully-automated framework for RBD detection consisting of automated sleep staging followed by RBD identifica

Externí odkaz: http://arxiv.org/abs/1811.04662

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SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging

Autor: Phan, Huy, Andreotti, Fernando, Cooray, Navin, Chén, Oliver Y., De Vos, Maarten

Automatic sleep staging has been often treated as a simple classification problem that aims at determining the label of individual target polysomnography (PSG) epochs one at a time. In this work, we tackle the task as a sequence-to-sequence classific

Externí odkaz: http://arxiv.org/abs/1809.10932

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Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification

Autor: Phan, Huy, Andreotti, Fernando, Cooray, Navin, Chén, Oliver Y., De Vos, Maarten

Correctly identifying sleep stages is important in diagnosing and treating sleep disorders. This work proposes a joint classification-and-prediction framework based on CNNs for automatic sleep staging, and, subsequently, introduces a simple yet effic

Externí odkaz: http://arxiv.org/abs/1805.06546

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