Electrooculography Dataset for Objective Spatial Navigation Assessment in Healthy Participants
Jan 1, 2025·
,,,,·
0 min read
Mobina Zibandehpoor
Fatemeh Alizadehziri
Arash Abbasi Larki
Sobhan Teymouri
Mehdi Delrobaei
Abstract
In the quest for understanding human executive function, eye movements represent a unique insight into how we process and comprehend our environment. Eye movements reveal patterns in how we focus, navigate, and make decisions across various contexts. The proposed dataset includes electrooculography (EOG) signals from 27 healthy subjects, capturing both vertical and horizontal eye movements. The recorded signals were obtained during the video-watching stage of the Leiden Navigation Test, designed to assess spatial navigation abilities. In addition to other data, the dataset includes scores from the Mini-Mental State Examination and the Wayfinding Questionnaire.
Type
Publication
Scientific Data. Nature
Status
Peer-reviewed
Open access
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!😜