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Automating the detection of REM sleep behaviour disorder

Abstract:

This study aims to develop automated diagnostic tools to aid in the identification of rapid-eye-movement (REM) sleep behaviour disorder (RBD). Those diagnosed with RBD enact their dreams and therefore present an abnormal characteristic of movement during REM sleep. Several methods have been proposed for RBD detection that use electromyogram (EMG) recordings and manually annotated sleep stages to objectively quantify abnormal REM movement. In this work we further develop these proven technique...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/embc.2018.8512539

Authors


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Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering
Sub department:
Biomedical Engineering
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Engineering
Sub department:
Biomedical Engineering
Role:
Author
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
Clinical Neurosciences
Role:
Author
ORCID:
0000-0002-5671-3881
More by this author
Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
Clinical Neurosciences
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author
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Publisher:
IEEE Publisher's website
Journal:
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Journal website
Publication date:
2018-10-29
Acceptance date:
2018-04-08
DOI:
ISSN:
1557-170X
Pmid:
30440668
Source identifiers:
948884
Language:
English
Pubs id:
pubs:948884
UUID:
uuid:f9c4a30d-c8e0-475a-b549-36cc855170f2
Local pid:
pubs:948884
Deposit date:
2019-07-31

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