Continuous gait monitoring discriminates community-dwelling mild Alzheimer's disease from cognitively normal controls.

ABSTRACT:

Introduction

Few studies have explored whether gait measured continuously within a community setting can identify individuals with Alzheimer's disease (AD). This study tests the feasibility of this method to identify individuals at the earliest stage of AD.

Methods

Mild AD (n = 38) and cognitively normal control (CNC; n = 48) participants from the University of Kansas Alzheimer's Disease Center Registry wore a GT3x+ accelerometer continuously for 7 days to assess gait. Penalized logistic regression with repeated five-fold cross-validation followed by adjusted logistic regression was used to identify gait metrics with the highest predictive performance in discriminating mild AD from CNC.

Results

Variability in step velocity and cadence had the highest predictive utilit

SUBMITTER: Varma VR 

PROVIDER: S-EPMC7864220 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature