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A Novel Multimodal System to Predict Agitation in People with Dementia Within Clinical Settings: A Proof of Concept by Badawi, Abeer; Elmoghazy, Somayya; Choudhury, Samira; Elgazzar, Sara; Elgazzar, Khalid; Burhan, Amer is a scholarly article available to read on EtoBox.

What is A Novel Multimodal System to Predict Agitation in People with Dementia Within Clinical Settings: A Proof of Concept about?

Dementia is a neurodegenerative condition that combines several diseases and impacts millions around the world and those around them. Although cognitive impairment is profoundly disabling, it is the noncognitive features of dementia, referred to as Neuropsychiatric Symptoms (NPS), that are most closely associated with a diminished quality of life. Agitation and aggression (AA) in people living with dementia (PwD) contribute to distress and increased healthcare demands. Current assessment methods rely on caregiver intervention and reporting of incidents, introducing subjectivity and bias. Artificial Intelligence (AI) and predictive algorithms offer a potential solution for detecting AA episodes in PwD when utilized in real-time. We present a 5-year study system that integrates a multimodal approach, utilizing the EmbracePlus wristband and a video detection system to predict AA in severe dementia patients. We conducted a pilot study with three participants at the Ontario Shores Mental Health Institute to validate the functionality of the system. The system collects and processes raw and digital biomarkers from the EmbracePlus wristband to accurately predict AA. The system also detect

Author

Badawi, Abeer; Elmoghazy, Somayya; Choudhury, Samira; Elgazzar, Sara; Elgazzar, Khalid; Burhan, Amer

Published

2024

Language

EN