Feasibility of assessing cognitive impairment via distributed camera network and privacy-preserving edge computing.

ABSTRACT:

Introduction

Mild cognitive impairment (MCI) involves cognitive decline beyond normal age and education expectations. It correlates with decreased socialization and increased aimless motion. We aim to automate detection of these behaviors for improved longitudinal monitoring.

Methods

We used a privacy-preserving distributed camera network to collect data from MCI patients in an indoor space. Movement and social interaction features were developed using this data to train machine learning algorithms to differentiate between higher and lower cognitive functioning MCI groups.

Results

A Wilcoxon rank-sum test showed significant differences between high- and low-functioning cohorts in the movement and social interaction features. Despite the absence of data linking each pe

SUBMITTER: Hegde C 

PROVIDER: S-EPMC11848627 | biostudies-literature | 2025 Jan-Mar

REPOSITORIES: biostudies-literature