Classification of MCI patients using vergence eye movements and pupil responses obtained during a visual oddball test

Aging and health research Pub Date : 2023-03-01 DOI:10.1016/j.ahr.2023.100121

Amin Hashemi , Oleksii Leonovych , Elizabeth Carolina Jiménez , Alba Sierra-Marcos , August Romeo , Patricia Bustos Valenzuala , Maria Solé Puig , Joan Lopez Moliner , Elisabet Tubau , Hans Supèr

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引用次数: 1

Abstract

In the current study, we tested the hypothesis that Mild Cognitive Impairment (MCI) patients can be identified based on the analysis of vergence eye movements and pupil responses. We recorded vergence and pupil responses in MCI patients (N = 22) and cognitive healthy elderly (N = 18) while performing a visual oddball task. Based on selected features, a classifier model computed probability scores predicting MCI. MCI patients were re-evaluated in a follow-up visit of 12–18 months. For validating the model, patients with Alzheimer's Disease (AD) (N = 9) were tested. High classification accuracy was obtained (AUC: 0.93). In addition, the probability scores showed significant predictive power of MCI conversion into possible AD. Our results show that MCI can be detected by assessing vergence and pupil responses during a simple and short task. Therefore, these responses could potentially be used as a marker tool for MCI diagnosis and to identify the risk of developing Alzheimer's Disease.

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在视觉怪球测试中获得的收敛眼动和瞳孔反应对MCI患者的分类

在本研究中，我们验证了轻度认知障碍(MCI)患者可以通过分析会聚眼动和瞳孔反应来识别的假设。我们记录了MCI患者(N = 22)和认知健康老年人(N = 18)在执行视觉怪球任务时的收敛和瞳孔反应。基于选择的特征，分类器模型计算预测MCI的概率分数。在12-18个月的随访中对MCI患者进行重新评估。为了验证模型，对阿尔茨海默病(AD)患者(N = 9)进行了测试。获得了较高的分类准确率(AUC: 0.93)。此外，概率得分显示MCI转化为可能的AD的显著预测能力。我们的研究结果表明，MCI可以通过评估在一个简单和短的任务中的收敛和瞳孔反应来检测。因此，这些反应可能被用作MCI诊断的标记工具，并确定发展为阿尔茨海默病的风险。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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