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• W2896087634 abstract "Assessment of challenging behaviors in dementia is important for intervention selection. Here, we describe the technical and experimental set-up, the feasibility as well as outcomes of automated sensor based assessment of long-term behavior of people with advanced dementia living in nursing homes. We conducted four weeks of multimodal sensor assessment together with real time observation of 17 residents with moderate to very severe dementia in nursing care units. Behavior of a subsample of 8 participants was further recorded by video-taping over four weeks during day hours. Sensors were mounted on the participants’ wrist and ankle, and measured motion, rotation as well as surrounding loudness level, light level and air pressure. For reference, residents' behavior was annotated in real time by trained observers using behavioral rating schemes. In addition, two independent raters annotated video material off-line. We assessed feasibility of sensor based assessment, safety of data acquisition, reliability of behavioral rating and the association of accelerometric signal with behavioral rating outcomes. Participants were in moderate to severe stages of dementia. Almost 100% of participants exhibited relevant levels of challenging behaviors. Only 11% of the recordings had been influenced by noncompliance of the participants. Implementation of the technology and observation platform in the routine procedures of the nursing home units was feasible, and identified a range of user related and hardware related implementation and handling challenges. Inter-reater-reliabiltiy was moderate to low for real-time assessment, but was high for off-line annotation of video material. Accelerometric motion features were found highly predictive for long-term behavioral features, representing an individual behavioral fingerprint of each participant. Our findings suggest that automated assessment of behavioral features is possible even in people with advanced stages of dementia. The automated and objective detection of challenging behaviors can help professional and family caregivers to identify early signs of behavioral changes and monitor effects of interventions to mitigate such behaviors. The ongoing InsideDem project plans to integrate automated behavior fingerprint detection into a digitalized expert system to aid professional and family caregivers in coping with challenging behaviors of people with dementia . Automated activity assessment and behavioral fingerprints of people with advanced dementia Upper panel: Cumulated activity levels of a group of people with advanced stages of dementia over two daysLower panel: Behavioral fingerprints from people with dementia in different behavioral categories (color coded, including agitation, agression, pacing) cumulated over two weeks as predicted by accelerometric sensors in 11 participants (test data set)." @default.
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• W2896087634 date "2018-07-01" @default.
• W2896087634 modified "2023-10-16" @default.
• W2896087634 title "F1‐05‐02: INSIDEDEM: TECHNOLOGY FOR MANAGING CHALLENGING BEHAVIOR IN DEMENTIA" @default.
• W2896087634 doi "https://doi.org/10.1016/j.jalz.2018.06.2320" @default.
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