Multimodal Classification of Sense-of-Direction Performance in Healthy Individuals from Trajectory and Head Motion During the Walking Corsi Test
Jan 1, 2026·
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0 min read
Mobina Zibandehpoor
Mehdi Delrobaei
Abstract
Sense of direction (SoD) is a stable individual trait that influences spatial behavior in everyday environments. While commonly assessed via self-report, this paper presents a multimodal, low-burden sensing framework to objectively estimate SoD in healthy individuals during a walking-based spatial task. Using only a wall-mounted camera and a head-worn inertial measurement unit, we reconstruct walking trajectories via pose estimation and capture head kinematics during the Walking Corsi Test (WalCT). Trajectory and head-motion features are fused at the participant level and filtered using a correlation threshold.
Type
Publication
12th International Conference on Web Research (ICWR)
Status
Peer-reviewed
Authors
Mobina Zibandehpoor
(she/her)
M.Sc. Researcher
Hi, I’m Mobina, an M.Sc. mechatronics researcher passionate about non-invasive assessment of human cognitive performance. My work sits at the intersection of computer vision, biosignal analysis, and machine learning, developing multimodal frameworks that combine vision-based pose estimation, IMU motion capture, and eye tracking for interpretable behavioral analysis. I enjoy designing algorithms and experimental systems that connect mechatronic instrumentation with real-world cognitive assessment.
Please reach out if you’re interested in collaborating on Human-Computer Interaction, biosignal analysis, or AI-driven behavioral assessment!😜