Investigates early cognitive decline in Alzheimer's disease, suggesting new screening methods.
This project investigates privacy-preserving, home-based IoT sensing as a source of digital behavioural biomarkers for early cognitive impairment and neuropsychiatric symptoms in Alzheimer’s disease (AD). Longitudinal in-home behavioural data will be analysed alongside clinical cognitive assessments, including MoCA and/or MMSE where available, and neuropsychiatric symptom measures. The study will identify temporal and behavioural patterns associated with apathy, anxiety, depression, and cognitive decline. Interpretable machine-learning models with leakage-resistant validation will be used to evaluate the potential of these digital biomarkers for early screening and continuous monitoring in community-dwelling older adults.
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Xiang Ji (2026) studied this question.
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