Daniol Mateusz, Hemmerling Daria, Sikora Jakub, Jemiolo Pawel, Wodzinski Marek, Wojcik-Pedziwiatr Magdalena
Annu Int Conf IEEE Eng Med Biol Soc. 2024 Jul;2024:1-4. doi: 10.1109/EMBC53108.2024.10782100.
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.
帕金森病是全球第二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功能来跟踪和评估眼动的系统。在本文中，我们呈现了一个医学场景，并概述了一个应用程序的开发，该应用程序旨在通过混合现实技术捕捉眼动信号，以评估神经退行性疾病。此外，我们介绍了一种从眼动分析中提取临床相关特征的流程，从医学角度描述了所提出系统的功能。该研究涉及一组健康对照个体和帕金森病患者，展示了所提出技术用于非侵入性监测眼动模式以诊断神经退行性疾病的可行性和潜力。临床相关性——迫切需要开发一种用于帕金森病的非侵入性生物标志物，以准确检测疾病的发作。这将允许在最早阶段及时引入神经保护治疗，并能够持续监测干预结果。检测眼动细微变化的能力有助于早期诊断，在更明显的症状出现之前提供关键的干预窗口。眼动追踪提供客观且可量化的生物标志物，确保对疾病进展和认知功能进行可靠评估。使用混合现实眼镜进行眼动分析是无线的，便于在家庭和医院环境中进行便捷评估。该方法的优势在于利用无需额外专门附件的硬件，通过个人眼镜即可进行检查。
