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000285366 037__ $$aDZNE-2026-00230
000285366 041__ $$aEnglish
000285366 1001_ $$aSchmitz, Lio$$b0
000285366 1112_ $$aPacific Symposium on Biocomputing 2026$$cKohala Coast$$d2026-01-03 - 2026-01-07$$wHawaii
000285366 245__ $$aTowards Automated Analysis of Gaze Behavior from Consumer VR Devices for Neurological Diagnosis
000285366 260__ $$bWORLD SCIENTIFIC$$c2025
000285366 29510 $$aBiocomputing 2026 : [Proceedings] - WORLD SCIENTIFIC, 2025. - ISBN 978-981-98-2474-8978-981-98-2475-5 - doi:10.1142/9789819824755_0016
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000285366 520__ $$aRecent studies have demonstrated that eye tracking is a valuable tool in the detection, classification and staging of neurodegenerative diseases such as Parkinson's Disease (PD). However, traditional methods for capturing gaze data often rely on expensive and non-engaging clinical equipment such as video-oculography, limiting their accessibility and scalability. In this work, we investigate the feasibility of using eye tracking data collected via consumer-grade virtual reality (VR) headsets to support neurological diagnostics in a more accessible and user-friendly manner.This approach enables large-scale, low-cost, and remote assessments, which are particularly valuable in early detection and monitoring of neurodegenerative conditions. We show that relevant oculomotor features extracted from VR-based eye tracking can be used for predictive assessment. Despite the inherent noise and lower precision of consumer devices, careful preprocessing and robust feature engineering, including deep learning embeddings, mitigate these limitations. Our results demonstrate that both handcrafted and learned features from gaze behavior enable promising levels of classification performance. This research represents an important step towards scalable, automated, and accessible diagnostic tools for neurodegenerative diseases using ubiquitous VR technology.
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000285366 7001_ $$aPlack, Markus$$b1
000285366 7001_ $$0P:(DE-2719)9001550$$aKoyak, Berkan$$b2$$udzne
000285366 7001_ $$0P:(DE-2719)9003280$$aUllah, Ehsan$$b3$$udzne
000285366 7001_ $$0P:(DE-2719)2812578$$aAziz, Ahmad$$b4$$udzne
000285366 7001_ $$aKlein, Reinhard$$b5
000285366 7001_ $$aLähner, Zorah$$b6
000285366 7001_ $$aDröge, Hannah$$b7
000285366 773__ $$a10.1142/9789819824755_0016
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000285366 9101_ $$0I:(DE-588)1065079516$$6P:(DE-2719)9001550$$aDeutsches Zentrum für Neurodegenerative Erkrankungen$$b2$$kDZNE
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000285366 9201_ $$0I:(DE-2719)5000071$$kAG Aziz$$lPopulation & Clinical Neuroepidemiology$$x0
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