Curve walking gait analysis using depth camera and machine learning for detecting cognitive impairment

Introduction

Early detection of cognitive impairment (CI), including MCI and Alzheimer's disease (AD), remains limited by the invasiveness and cost of current diagnostic tools. While gait analysis is a promising alternative, most studies focus on straight-path walking, which may miss subtle motor-cognitive deficits. We hypothesized that curve walking-especially under dual-task (DT) conditions-would better expose early CI-related changes. Combined with machine learning, this approach offers a low-cost, non-invasive tool to distinguish healthy controls (HC), MCI, and AD.