Evaluation of Visuospatial Ability in Elderly Adults Using Eye Tracking and Virtual Reality Content

Early detection of mild cognitive impairment (MCI) is essential for preventing progression to dementia. Conventional neuropsychological tests, such as cube copying and clock drawing, are widely used to assess visuospatial and executive functions; however, these assessments rely largely on qualitative observation by clinicians, which may limit their objectivity. Therefore, a quantitative method for objectively evaluating visuospatial function is desirable. This study develops and validates a virtual reality (VR)-based assessment using eye-tracking that enables objective differentiation between healthy elderly adults and individuals suspected of having MCI. VR content presenting periodic depth stimuli was developed, and gaze behavior was recorded using a head-mounted display equipped with an eye-tracking system. Changes in interpupillary distance induced by depth perception were analyzed to derive quantitative indices, including the coefficient of determination ( R 2 ) obtained using sinusoidal fitting and spectral power in the frequency domain. Experiments were conducted with elderly participants consisting of a healthy group and individuals suspected of having MCI, as determined based on the Japanese version of the Montreal Cognitive Assessment. Significant differences were observed between the groups ( p =0.026), and linear discriminant analysis achieved accurate classification, with no misclassification in the healthy group and two misclassifications in the suspected MCI group. These findings indicate that the proposed method enables objective and quantitative evaluation of visuospatial function and may contribute to the early detection and screening of MCI.

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Publication Details

Journal
Journal of Advanced Computational Intelligence and Intelligent Informatics
Published
2026-09-19
DOI
https://doi.org/10.20965/jaciii.2026.p1526
Primary Topic
Dementia and Cognitive Impairment Research
Type
article
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article

Evaluation of Visuospatial Ability in Elderly Adults Using Eye Tracking and Virtual Reality Content

Tomiko Takeuchi, Fumiya Kinoshita, Kansuke Kawaguchi
Journal of Advanced Computational Intelligence and Intelligent Informatics
Dementia and Cognitive Impairment Research
article

Evaluation of Visuospatial Ability in Elderly Adults Using Eye Tracking and Virtual Reality Content

Tomiko Takeuchi, Fumiya Kinoshita, Kansuke Kawaguchi
article en

Abstract

Early detection of mild cognitive impairment (MCI) is essential for preventing progression to dementia. Conventional neuropsychological tests, such as cube copying and clock drawing, are widely used to assess visuospatial and executive functions; however, these assessments rely largely on qualitative observation by clinicians, which may limit their objectivity. Therefore, a quantitative method for objectively evaluating visuospatial function is desirable. This study develops and validates a virtual reality (VR)-based assessment using eye-tracking that enables objective differentiation between healthy elderly adults and individuals suspected of having MCI. VR content presenting periodic depth stimuli was developed, and gaze behavior was recorded using a head-mounted display equipped with an eye-tracking system. Changes in interpupillary distance induced by depth perception were analyzed to derive quantitative indices, including the coefficient of determination ( R 2 ) obtained using sinusoidal fitting and spectral power in the frequency domain. Experiments were conducted with elderly participants consisting of a healthy group and individuals suspected of having MCI, as determined based on the Japanese version of the Montreal Cognitive Assessment. Significant differences were observed between the groups ( p =0.026), and linear discriminant analysis achieved accurate classification, with no misclassification in the healthy group and two misclassifications in the suspected MCI group. These findings indicate that the proposed method enables objective and quantitative evaluation of visuospatial function and may contribute to the early detection and screening of MCI.

Journal of Advanced Computational Intelligence and Intelligent InformaticsVol. 30(5)
Mie University (JP), Toyama Prefectural University (JP)
Reduced inequalities
Openalex Percentile: Top 10%
Dementia and Cognitive Impairment Research
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