Parkinson's disease ranks as the second most prevalent neurodegenerative disorder globally. This research aims to develop a system leveraging Mixed Reality capabilities for tracking and assessing eye movements. In this paper, we present a medical scenario and outline the development of an application designed to capture eye-tracking signals through Mixed Reality technology for the evaluation of neurodegenerative diseases. Additionally, we introduce a pipeline for extracting clinically relevant features from eye-gaze analysis, describing the capabilities of the proposed system from a medical perspective. The study involved a cohort of healthy control individuals and patients suffering from Parkinson's disease, showcasing the feasibility and potential of the proposed technology for non-intrusive monitoring of eye movement patterns for the diagnosis of neurodegenerative diseases. Clinical relevance - Developing a non-invasive biomarker for Parkinson's disease is urgently needed to accurately detect the disease's onset. This would allow for the timely introduction of neuroprotective treatment at the earliest stage and enable the continuous monitoring of intervention outcomes. The ability to detect subtle changes in eye movements allows for early diagnosis, offering a critical window for intervention before more pronounced symptoms emerge. Eye tracking provides objective and quantifiable biomarkers, ensuring reliable assessments of disease progression and cognitive function. The eye gaze analysis using Mixed Reality glasses is wireless, facilitating convenient assessments in both home and hospital settings. The approach offers the advantage of utilizing hardware that requires no additional specialized attachments, enabling examinations through personal eyewear.

翻译：帕金森病是全球第二大常见的神经退行性疾病。本研究旨在开发一种利用混合现实技术追踪与评估眼动功能的系统。本文提出一个医疗应用场景，并概述了为评估神经退行性疾病而设计的、通过混合现实技术采集眼动追踪信号的应用程序开发方案。此外，我们引入了一套从眼动凝视分析中提取临床相关特征的流程，从医学角度阐述了所提出系统的功能。研究纳入了健康对照组个体与帕金森病患者队列，展示了该技术在通过无创监测眼动模式诊断神经退行性疾病方面的可行性与潜力。临床意义——当前亟需开发一种非侵入性的帕金森病生物标志物以实现对疾病发作的精准检测。这将有助于在疾病最早期阶段及时开展神经保护性治疗，并实现对干预效果的持续监测。检测眼动细微变化的能力可实现早期诊断，为在更显著症状出现前进行干预提供关键窗口期。眼动追踪技术可提供客观且可量化的生物标志物，确保对疾病进展与认知功能进行可靠评估。基于混合现实眼镜的眼动凝视分析采用无线技术，便于在家庭和医院环境中进行便捷评估。该方法的优势在于无需额外专用附件即可利用硬件设备，支持通过个人佩戴的眼镜完成检测。