Electrooculography Dataset for Objective Spatial Navigation Assessment in Healthy Participants

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 electroocu...

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Main Authors: Mobina Zibandehpoor, Fatemeh Alizadehziri, Arash Abbasi Larki, Sobhan Teymouri, Mehdi Delrobaei
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Data
Online Access:https://doi.org/10.1038/s41597-025-04879-z
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author Mobina Zibandehpoor
Fatemeh Alizadehziri
Arash Abbasi Larki
Sobhan Teymouri
Mehdi Delrobaei
author_facet Mobina Zibandehpoor
Fatemeh Alizadehziri
Arash Abbasi Larki
Sobhan Teymouri
Mehdi Delrobaei
author_sort Mobina Zibandehpoor
collection DOAJ
description 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. The dataset comprises carefully curated components, including relevant information, the Mini-Mental State Examination scores, and the Wayfinding Questionnaire scores, encompassing navigation, orientation, distance estimation, spatial anxiety, as well as raw and processed EOG signals. These assessments contribute more information about the participants’ cognitive function and navigational abilities. This dataset can be valuable for researchers investigating spatial navigation abilities through EOG signal analysis.
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spelling doaj-art-74460f999e6b42e7a02e71d0f3d9b2022025-08-20T03:08:02ZengNature PortfolioScientific Data2052-44632025-04-011211810.1038/s41597-025-04879-zElectrooculography Dataset for Objective Spatial Navigation Assessment in Healthy ParticipantsMobina Zibandehpoor0Fatemeh Alizadehziri1Arash Abbasi Larki2Sobhan Teymouri3Mehdi Delrobaei4Mechatronics Department, Faculty of Electrical Engineering, K. N. Toosi University of TechnologyMechatronics Department, Faculty of Electrical Engineering, K. N. Toosi University of TechnologyMechatronics Department, Faculty of Electrical Engineering, K. N. Toosi University of TechnologyMechatronics Department, Faculty of Electrical Engineering, K. N. Toosi University of TechnologyMechatronics Department, Faculty of Electrical Engineering, K. N. Toosi University of TechnologyAbstract 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. The dataset comprises carefully curated components, including relevant information, the Mini-Mental State Examination scores, and the Wayfinding Questionnaire scores, encompassing navigation, orientation, distance estimation, spatial anxiety, as well as raw and processed EOG signals. These assessments contribute more information about the participants’ cognitive function and navigational abilities. This dataset can be valuable for researchers investigating spatial navigation abilities through EOG signal analysis.https://doi.org/10.1038/s41597-025-04879-z
spellingShingle Mobina Zibandehpoor
Fatemeh Alizadehziri
Arash Abbasi Larki
Sobhan Teymouri
Mehdi Delrobaei
Electrooculography Dataset for Objective Spatial Navigation Assessment in Healthy Participants
Scientific Data
title Electrooculography Dataset for Objective Spatial Navigation Assessment in Healthy Participants
title_full Electrooculography Dataset for Objective Spatial Navigation Assessment in Healthy Participants
title_fullStr Electrooculography Dataset for Objective Spatial Navigation Assessment in Healthy Participants
title_full_unstemmed Electrooculography Dataset for Objective Spatial Navigation Assessment in Healthy Participants
title_short Electrooculography Dataset for Objective Spatial Navigation Assessment in Healthy Participants
title_sort electrooculography dataset for objective spatial navigation assessment in healthy participants
url https://doi.org/10.1038/s41597-025-04879-z
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