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Sensing a problem: Proof of concept for characterizing and predicting agitation

INTRODUCTION: Agitation, experienced by patients with dementia, is difficult to manage and stressful for caregivers. Currently, agitation is primarily assessed by caregivers or clinicians based on self‐report or very brief periods of observation. This limits availability of comprehensive or sensitiv...

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Autores principales: Au‐Yeung, Wan‐Tai M., Miller, Lyndsey, Beattie, Zachary, Dodge, Hiroko H., Reynolds, Christina, Vahia, Ipsit, Kaye, Jeffrey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7443743/
https://www.ncbi.nlm.nih.gov/pubmed/32864417
http://dx.doi.org/10.1002/trc2.12079
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author Au‐Yeung, Wan‐Tai M.
Miller, Lyndsey
Beattie, Zachary
Dodge, Hiroko H.
Reynolds, Christina
Vahia, Ipsit
Kaye, Jeffrey
author_facet Au‐Yeung, Wan‐Tai M.
Miller, Lyndsey
Beattie, Zachary
Dodge, Hiroko H.
Reynolds, Christina
Vahia, Ipsit
Kaye, Jeffrey
author_sort Au‐Yeung, Wan‐Tai M.
collection PubMed
description INTRODUCTION: Agitation, experienced by patients with dementia, is difficult to manage and stressful for caregivers. Currently, agitation is primarily assessed by caregivers or clinicians based on self‐report or very brief periods of observation. This limits availability of comprehensive or sensitive enough reporting to detect early signs of agitation or identify its precipitants. The purpose of this article is to provide proof of concept for characterizing and predicting agitation using a system that continuously monitors patients’ activities and living environment within memory care facilities. METHODS: Continuous and unobtrusive monitoring of a participant is achieved using behavioral sensors, which include passive infrared motion sensors, door contact sensors, a wearable actigraphy device, and a bed pressure mat sensor installed in the living quarters of the participant. Environmental sensors are also used to continuously assess temperature, light, sound, and humidity. Episodes of agitation are reported by nursing staff. Data collected for 138 days were divided by 8‐hour nursing shifts. Features from agitated shifts were compared to those from non‐agitated shifts using t‐tests. RESULTS: A total of 37 episodes of agitation were reported for a male participant, aged 64 with Alzheimer's disease, living in a memory care unit. Participant activity metrics (eg, transitions within the living room, sleep scores from the bedmat, and total activity counts from the actigraph) significantly correlated with occurrences of agitation at night (P < 0.05). Environmental variables (eg, humidity) also correlated with the occurrences of agitation at night (P < 0.05). Higher activity levels were also observed in the evenings before agitated nights. DISCUSSION: A platform of sensors used for unobtrusive and continuous monitoring of participants with dementia and their living space seems feasible and shows promise for characterization of episodes of agitation and identification of behavioral and environmental precipitants of agitation.
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spelling pubmed-74437432020-08-28 Sensing a problem: Proof of concept for characterizing and predicting agitation Au‐Yeung, Wan‐Tai M. Miller, Lyndsey Beattie, Zachary Dodge, Hiroko H. Reynolds, Christina Vahia, Ipsit Kaye, Jeffrey Alzheimers Dement (N Y) Research Articles INTRODUCTION: Agitation, experienced by patients with dementia, is difficult to manage and stressful for caregivers. Currently, agitation is primarily assessed by caregivers or clinicians based on self‐report or very brief periods of observation. This limits availability of comprehensive or sensitive enough reporting to detect early signs of agitation or identify its precipitants. The purpose of this article is to provide proof of concept for characterizing and predicting agitation using a system that continuously monitors patients’ activities and living environment within memory care facilities. METHODS: Continuous and unobtrusive monitoring of a participant is achieved using behavioral sensors, which include passive infrared motion sensors, door contact sensors, a wearable actigraphy device, and a bed pressure mat sensor installed in the living quarters of the participant. Environmental sensors are also used to continuously assess temperature, light, sound, and humidity. Episodes of agitation are reported by nursing staff. Data collected for 138 days were divided by 8‐hour nursing shifts. Features from agitated shifts were compared to those from non‐agitated shifts using t‐tests. RESULTS: A total of 37 episodes of agitation were reported for a male participant, aged 64 with Alzheimer's disease, living in a memory care unit. Participant activity metrics (eg, transitions within the living room, sleep scores from the bedmat, and total activity counts from the actigraph) significantly correlated with occurrences of agitation at night (P < 0.05). Environmental variables (eg, humidity) also correlated with the occurrences of agitation at night (P < 0.05). Higher activity levels were also observed in the evenings before agitated nights. DISCUSSION: A platform of sensors used for unobtrusive and continuous monitoring of participants with dementia and their living space seems feasible and shows promise for characterization of episodes of agitation and identification of behavioral and environmental precipitants of agitation. John Wiley and Sons Inc. 2020-08-24 /pmc/articles/PMC7443743/ /pubmed/32864417 http://dx.doi.org/10.1002/trc2.12079 Text en © 2020 The Authors. Alzheimer's & Dementia: Translational Research & Clinical Interventions published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research Articles
Au‐Yeung, Wan‐Tai M.
Miller, Lyndsey
Beattie, Zachary
Dodge, Hiroko H.
Reynolds, Christina
Vahia, Ipsit
Kaye, Jeffrey
Sensing a problem: Proof of concept for characterizing and predicting agitation
title Sensing a problem: Proof of concept for characterizing and predicting agitation
title_full Sensing a problem: Proof of concept for characterizing and predicting agitation
title_fullStr Sensing a problem: Proof of concept for characterizing and predicting agitation
title_full_unstemmed Sensing a problem: Proof of concept for characterizing and predicting agitation
title_short Sensing a problem: Proof of concept for characterizing and predicting agitation
title_sort sensing a problem: proof of concept for characterizing and predicting agitation
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7443743/
https://www.ncbi.nlm.nih.gov/pubmed/32864417
http://dx.doi.org/10.1002/trc2.12079
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