DoctorPupil: A Virtual Reality System for Parkinson's Diagnosis Through Task-Evoked Pupil Response

Parkinson's Disease (PD) is one of the most critical neurodegenerative diseases, yet there is no cure for it, and the state-of-the-art treatment is to slow its progression. Thus, the earlier a patient with PD is recognized, the better he can be treated. Our project joins the research effort that aims to support early PD diagnosis by designing a Virtual Reality (VR)-based system to monitor pupil diameter patterns as new biomarkers (e.g., Pupil Light Reflex and Task-evoked Pupil Response) and provide early warning of potential PD onset. A follow-up experiment with 55 participants shows that the accuracy of recognizing early PD from healthy controls could reach 0.8942. Our study shows early results of a promising research direction that leverages VR-based technology to non-intrusively recognize patterns and provide alerts to early PD patients who would otherwise not know their symptoms until much later.

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Institutions

Publication Details

Journal
IEEE Journal of Biomedical and Health Informatics
Published
2025-01-22
DOI
https://doi.org/10.1109/jbhi.2025.3532695
Citations
2
Primary Topic
Stroke Rehabilitation and Recovery
Type
article
Field-Weighted Citation Impact
2.05

Funders

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article

DoctorPupil: A Virtual Reality System for Parkinson's Diagnosis Through Task-Evoked Pupil Response

Xucheng Zhang, Xiangmin Fan, Feng Tian, Dakuo Wang et al.
2 citations
IEEE Journal of Biomedical and Health Informatics
Stroke Rehabilitation and Recovery
2.05
article

DoctorPupil: A Virtual Reality System for Parkinson's Diagnosis Through Task-Evoked Pupil Response

Xucheng Zhang, Xiangmin Fan, Feng Tian, Dakuo Wang, Jing Zhao, Xinjin Li, Zhirong Wan, Yuxin Liu, Wei Sun
article en
2 citations

Abstract

Parkinson's Disease (PD) is one of the most critical neurodegenerative diseases, yet there is no cure for it, and the state-of-the-art treatment is to slow its progression. Thus, the earlier a patient with PD is recognized, the better he can be treated. Our project joins the research effort that aims to support early PD diagnosis by designing a Virtual Reality (VR)-based system to monitor pupil diameter patterns as new biomarkers (e.g., Pupil Light Reflex and Task-evoked Pupil Response) and provide early warning of potential PD onset. A follow-up experiment with 55 participants shows that the accuracy of recognizing early PD from healthy controls could reach 0.8942. Our study shows early results of a promising research direction that leverages VR-based technology to non-intrusively recognize patterns and provide alerts to early PD patients who would otherwise not know their symptoms until much later.

IEEE Journal of Biomedical and Health InformaticsVol. 29(8)
Northeastern University (US), Cambridge Scientific (United States) (US), Aerospace Center Hospital (CN), iQIYI (China) (CN), Institute of Software (CN)
National Natural Science Foundation of China, National Science and Technology Major Project
Openalex Percentile: Top 15%
Stroke Rehabilitation and Recovery
2.05
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DoctorPupil: A Virtual Reality System for Parkinson's Diagnosis Through Task-Evoked Pupil Response — Xucheng Zhang, Xiangmin Fan, et al. · IEEE Journal of Biomedical and Health Informatics (2025) | TGRS Research Map | TGRS