TY - JOUR
T1 - Sensing a problem
T2 - Proof of concept for characterizing and predicting agitation
AU - Au-Yeung, Wan Tai M.
AU - Miller, Lyndsey
AU - Beattie, Zachary
AU - Dodge, Hiroko H.
AU - Reynolds, Christina
AU - Vahia, Ipsit
AU - Kaye, Jeffrey
N1 - Funding Information:
Thank you to the staff at Pacific Gardens Alzheimer's Special Care Center, Portland, OR. Supported by National Institute on Aging (NIA) grants: P30 AG008017; P30 AG066518; P30 AG024978; U2CAG0543701.
Publisher Copyright:
© 2020 The Authors. Alzheimer's & Dementia: Translational Research & Clinical Interventions published by Wiley Periodicals, Inc. on behalf of Alzheimer's Association.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - actigraphy
KW - agitation
KW - bed pressure mat
KW - environmental sensing
KW - later-stage dementia
KW - motion sensor
KW - multimodal sensing
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U2 - 10.1002/trc2.12079
DO - 10.1002/trc2.12079
M3 - Article
AN - SCOPUS:85095954657
SN - 2352-8737
VL - 6
JO - Alzheimer's and Dementia: Translational Research and Clinical Interventions
JF - Alzheimer's and Dementia: Translational Research and Clinical Interventions
IS - 1
M1 - e12079
ER -