Citation

Khan SS, Ye B, Taati B, Mihailidis A. Alzheimers Dement. 2018; 14(6): 824-832.

Affiliation

University of Toronto, Toronto, ON, Canada; Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada; AGE-WELL Network of Centres of Excellence, Toronto, ON, Canada.

Copyright

(Copyright © 2018, Alzheimer's Association, Publisher Elsevier Publishing)

DOI

10.1016/j.jalz.2018.02.004

PMID

29571749

Abstract

Agitation and aggression are among the most challenging symptoms of dementia. Agitated persons with dementia can harm themselves, their caregivers, or other patients in a care facility. Automatic detection of agitation would be useful to alert caregivers so that appropriate interventions can be performed. The building blocks in the automatic detection of agitation and aggression are appropriate sensing platforms and generalized predictive models. In this article, we perform a systematic review of studies that use different types of sensors to detect agitation and aggression in persons with dementia. We conclude that actigraphy shows some evidence of correlation with incidences of agitation and aggression; however, multimodal sensing has not been fully evaluated for this purpose. Based on this systematic review, we provide guidelines and recommendations for future research directions in this field.

Copyright © 2018. Published by Elsevier Inc.

Language: en

Keywords

Aggression; Agitation; Dementia; Machine learning; Sensor