Altered Motor Activity Patterns within 10-Minute Timescale Predict Incident Clinical Alzheimer's Disease.

ABSTRACT:

Background

Fractal motor activity regulation (FMAR), characterized by self-similar temporal patterns in motor activity across timescales, is robust in healthy young humans but degrades with aging and in Alzheimer's disease (AD).

Objective

To determine the timescales where alterations of FMAR can best predict the clinical onset of AD.

Methods

FMAR was assessed from actigraphy at baseline in 1,077 participants who had annual follow-up clinical assessments for up to 15 years. Survival analysis combined with deep learning (DeepSurv) was used to examine how baseline FMAR at different timescales from 3 minutes up to 6 hours contributed differently to the risk for incident clinical AD.

Results

Clinical AD occurred in 270 participants during the follow-up. DeepSurv ide

SUBMITTER: Sun H 

PROVIDER: S-EPMC10977378 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature