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Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit

Patients in critical care settings often require continuous and multifaceted monitoring. However, current clinical monitoring practices fail to capture important functional and behavioral indices such as mobility or agitation. Recent advances in non-invasive sensing technology, high throughput compu...

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Autores principales: Davoudi, Anis, Shickel, Benjamin, Tighe, Patrick James, Bihorac, Azra, Rashidi, Parisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9152012/
https://www.ncbi.nlm.nih.gov/pubmed/35656333
http://dx.doi.org/10.3389/fdgth.2022.773387
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author Davoudi, Anis
Shickel, Benjamin
Tighe, Patrick James
Bihorac, Azra
Rashidi, Parisa
author_facet Davoudi, Anis
Shickel, Benjamin
Tighe, Patrick James
Bihorac, Azra
Rashidi, Parisa
author_sort Davoudi, Anis
collection PubMed
description Patients in critical care settings often require continuous and multifaceted monitoring. However, current clinical monitoring practices fail to capture important functional and behavioral indices such as mobility or agitation. Recent advances in non-invasive sensing technology, high throughput computing, and deep learning techniques are expected to transform the existing patient monitoring paradigm by enabling and streamlining granular and continuous monitoring of these crucial critical care measures. In this review, we highlight current approaches to pervasive sensing in critical care and identify limitations, future challenges, and opportunities in this emerging field.
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spelling pubmed-91520122022-06-01 Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit Davoudi, Anis Shickel, Benjamin Tighe, Patrick James Bihorac, Azra Rashidi, Parisa Front Digit Health Digital Health Patients in critical care settings often require continuous and multifaceted monitoring. However, current clinical monitoring practices fail to capture important functional and behavioral indices such as mobility or agitation. Recent advances in non-invasive sensing technology, high throughput computing, and deep learning techniques are expected to transform the existing patient monitoring paradigm by enabling and streamlining granular and continuous monitoring of these crucial critical care measures. In this review, we highlight current approaches to pervasive sensing in critical care and identify limitations, future challenges, and opportunities in this emerging field. Frontiers Media S.A. 2022-05-17 /pmc/articles/PMC9152012/ /pubmed/35656333 http://dx.doi.org/10.3389/fdgth.2022.773387 Text en Copyright © 2022 Davoudi, Shickel, Tighe, Bihorac and Rashidi. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Digital Health
Davoudi, Anis
Shickel, Benjamin
Tighe, Patrick James
Bihorac, Azra
Rashidi, Parisa
Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit
title Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit
title_full Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit
title_fullStr Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit
title_full_unstemmed Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit
title_short Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit
title_sort potentials and challenges of pervasive sensing in the intensive care unit
topic Digital Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9152012/
https://www.ncbi.nlm.nih.gov/pubmed/35656333
http://dx.doi.org/10.3389/fdgth.2022.773387
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