Laboratory of Medical Physics and Digital Innovation, School of Medicine, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece.
Memory Disorders and Rare Dementias Unit, 1st Department of Neurology, Eginiteion University Hospital, National and Kapodistrian University of Athens, 15772 Athens, Greece.
Sensors (Basel). 2021 Aug 26;21(17):5756. doi: 10.3390/s21175756.
Conventional clinical cognitive assessment has its limitations, as evidenced by the environmental shortcomings of various neuropsychological tests conducted away from an older person's everyday environment. Recent research activities have focused on transferring screening tests to computerized forms, as well as on developing short screening tests for screening large populations for cognitive impairment. The purpose of this study was to present an exergaming platform, which was widely trialed (116 participants) to collect in-game metrics (built-in game performance measures). The potential correlation between in-game metrics and cognition was investigated in-depth by scrutinizing different in-game metrics. The predictive value of high-resolution monitoring games was assessed by correlating it with classical neuropsychological tests; the area under the curve (AUC) in the receiver operating characteristic (ROC) analysis was calculated to determine the sensitivity and specificity of the method for detecting mild cognitive impairment (MCI). Classification accuracy was calculated to be 73.53% when distinguishing between MCI and normal subjects, and 70.69% when subjects with mild dementia were also involved. The results revealed evidence that careful design of serious games, with respect to in-game metrics, could potentially contribute to the early and unobtrusive detection of cognitive decline.
传统的临床认知评估有其局限性,这体现在各种神经心理测试在老年人日常生活环境之外进行时存在环境缺陷。最近的研究活动集中在将筛选测试转移到计算机化形式上,以及开发用于筛选大量人群认知障碍的简短筛选测试上。本研究旨在介绍一种游戏化平台,该平台经过广泛试用(116 名参与者),以收集游戏内指标(内置游戏表现衡量标准)。通过仔细研究不同的游戏内指标,深入探讨了游戏内指标与认知之间的潜在相关性。通过将高分辨率监测游戏与经典神经心理学测试相关联,评估了其对高分辨率监测游戏的预测价值;通过计算接收者操作特征(ROC)分析中的曲线下面积(AUC),确定该方法检测轻度认知障碍(MCI)的敏感性和特异性。当区分 MCI 和正常受试者时,分类准确率为 73.53%,当还涉及轻度痴呆症患者时,分类准确率为 70.69%。结果表明,认真设计游戏内指标的严肃游戏可能有助于早期、非侵入性地检测认知能力下降。