Objective Assessment of Navigation Trajectory in Walking Corsi Test Using Pose Estimation Algorithms

This study utilizes pose estimation algorithms to present a novel objective assessment of navigation trajectories in the walking Corsi test, known as a visuospatial working memory assessment task. Spatial navigation is critical in cognitive assessments, especially for detecting impairments in neurodegenerative conditions such as Alzheimer’s disease. By leveraging the OpenPose model, this approach tracks specific body keypoints, primarily focusing on the left ankle, to monitor and evaluate participant movement during the walking Corsi test. A Kalman filter was applied to enhance the accuracy of keypoint tracking, refining the model’s output by reducing noise and compensating for motion inaccuracies.