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Likelihood-based artefact detection in continuously-acquired patient vital signs

Abstract:

Robust continuous monitoring of patient vital signs (VS) is limited by artefactual data yielding measurements that are not representative of the patient’s physiology. These artefacts are typified by several distinct “archetypes”. We present several of these archetypal artefacts for heart rate (HR) monitoring, and propose a light weight, real-time algorithm to remove the majority of these artefacts. Most artefacts are not identifiable by their values in absolute terms, but instead by their val...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1109/EMBC.2017.8037279

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Institution:
University of Oxford
Oxford college:
St Cross College
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Institution:
University of Oxford
Division:
MSD
Department:
NDORMS
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
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Funding agency for:
Colopy, G
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Funding agency for:
Clifton, D
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Publisher:
IEEE Publisher's website
Journal:
Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings Journal website
Pages:
2146-2149
Host title:
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Publication date:
2017-09-14
Acceptance date:
2017-05-05
DOI:
ISSN:
1558-4615
Source identifiers:
694230
ISBN:
9781509028092
Pubs id:
pubs:694230
UUID:
uuid:1bfbe820-1401-462d-b084-c74ef2e66b61
Local pid:
pubs:694230
Deposit date:
2017-05-12

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