| Intracranial pressure signal morphology: real-time tracking. | |
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MedLine Citation:
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PMID: 22481746 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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The waveform morphology of intracranial pressure (ICP) pulses holds essential information about intracranial and cerebrovascular pathophysiologies. Automatic analysis of the ICP waveforms may help to predict abnormal increase of ICP and thus prevent severe complications in patients treated for traumatic brain injuries (TBIs). This article describes a probabilistic framework to track the ICP waveform morphology in real time. The model represents the correlation between different ICP morphological metrics extracted within a single pulse as well as the temporal dependence of metrics extracted between successive pulses. Morphological tracking is solved using Bayesian inference in a dynamic graphical model that associates a random variable to each morphological metric. |
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Authors:
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Fabien Scalzo; Marvin Bergsneider; Paul Vespa; Neil Martin; Xiao Hu |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: IEEE pulse Volume: 3 ISSN: 2154-2287 ISO Abbreviation: IEEE Pulse Publication Date: 2012 Mar |
Date Detail:
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Created Date: 2012-04-06 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 101541727 Medline TA: IEEE Pulse Country: United States |
Other Details:
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Languages: eng Pagination: 49-52 Citation Subset: IM |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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