Comparative Analysis of Actigraphy-Derived Indices in Alzheimer’s Disease and Healthy Controls Using UK Biobank Data
TL;DR
It is indicated that actigraphy can capture measurable differences in activity and circadian patterns in AD, supporting its potential as a non-invasive tool for screening or monitoring disease-related changes.
Abstract
Disrupted circadian rhythms are common in Alzheimer’s disease (AD) and are associated with sleep fragmentation, behavioural symptoms, and cognitive decline. Despite this, objective characterization of circadian and rest–activity disturbances in AD using real-world wearable sensor data remains limited. Actigraphy, derived from wrist-worn accelerometry, offers a non-invasive method for quantifying habitual activity patterns and circadian organization over extended monitoring periods. Using raw 7-day wrist-worn accelerometry data from the UK Biobank, this study compared rest-activity patterns between 50 participants with AD and 50 healthy controls. Data were processed to extract circadian and activity metrics and group differences were assessed using appropriate statistical tests. AD participants exhibited lower overall activity (Mesor), most active 10 hours (M10) and least active 5 hours (L5) compared with controls, while variability in acrophase was greater in the AD group, suggesting disrupted circadian timing. Visual inspection of 24-hour ENMO profiles confirmed attenuated day-night activity contrast in AD participants. These findings indicate that actigraphy can capture measurable differences in activity and circadian patterns in AD, supporting its potential as a non-invasive tool for screening or monitoring disease-related changes.