Physiological Profiling of Agitation in Dementia: Insights From Wearable Sensor Data

Author:

Davidoff Hannah12ORCID,Van Kraaij Alex3ORCID,Van den Bulcke Laura45ORCID,Lutin Erika2ORCID,Vandenbulcke Mathieu45ORCID,Van Helleputte Nick2ORCID,De Vos Maarten16ORCID,Van Hoof Chris13ORCID,Van Den Bossche Maarten45ORCID

Affiliation:

1. Department of Electrical Engineering, ESAT, KU Leuven , Heverlee , Belgium

2. Imec , Heverlee , Belgium

3. OnePlanet Research Center , Wageningen , Netherlands

4. Geriatric Psychiatry, University Psychiatric Center KU Leuven , Leuven , Belgium

5. Neuropsychiatry, Research Group Psychiatry, Department of Neurosciences, Leuven Brain Institute, KU Leuven , Leuven , Belgium

6. Department of Development and Regeneration, Faculty of Medicine, KU Leuven , Leuven , Belgium

Abstract

Abstract Background and Objectives The number of people with dementia is expected to triple to 152 million in 2050, with 90% having accompanying behavioral and psychological symptoms (BPSD). Agitation is among the most critical BPSD and can lead to decreased quality of life for people with dementia and their caregivers. This study aims to explore objective quantification of agitation in people with dementia by analyzing the relationships between physiological and movement data from wearables and observational measures of agitation. Research Design and Methods The data presented here is from 30 people with dementia, each included for 1 week, collected following our previously published multimodal data collection protocol. This observational protocol has a cross-sectional repeated measures design, encompassing data from both wearable and fixed sensors. Generalized linear mixed models were used to quantify the relationship between data from different wearable sensor modalities and agitation, as well as motor and verbal agitation specifically. Results Several features from wearable data are significantly associated with agitation, at least the p < .05 level (absolute β: 0.224-0.753). Additionally, different features are informative depending on the agitation type or the patient the data were collected from. Adding context with key confounding variables (time of day, movement, and temperature) allows for a clearer interpretation of feature differences when a person with dementia is agitated. Discussion and Implications The features shown to be significantly different, across the study population, suggest possible autonomic nervous system activation when agitated. Differences when splitting the data by agitation type point toward a need for future detection models to tailor to the primary type of agitation expressed. Finally, patient-specific differences in features indicate a need for patient- or group-level model personalization. The findings reported in this study both reinforce and add to the fundamental understanding of and can be used to drive the objective quantification of agitation.

Funder

Province of Gelderland

KU Leuven

King Baudouin Foundation of Belgium

KU Leuven and the University of Melbourne

University Hospitals Leuven

Publisher

Oxford University Press (OUP)

Reference54 articles.

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