Muurling Marijn, de Boer Casper, Vairavan Srinivasan, Harms Robbert L, Chadha Antonella Santuccione, Tarnanas Ioannis, Luis Estefania Vilarino, Religa Dorota, Gjestsen Martha Therese, Galluzzi Samantha, Ibarria Sala Marta, Koychev Ivan, Hausner Lucrezia, Gkioka Mara, Aarsland Dag, Visser Pieter Jelle, Brem Anna-Katharine
Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
NPJ Digit Med. 2023 Dec 18;6(1):234. doi: 10.1038/s41746-023-00978-6.
Augmented reality (AR) apps, in which the virtual and real world are combined, can recreate instrumental activities of daily living (IADL) and are therefore promising to measure cognition needed for IADL in early Alzheimer's disease (AD) both in the clinic and in the home settings. The primary aim of this study was to distinguish and classify healthy controls (HC) from participants with AD pathology in an early AD stage using an AR app. The secondary aims were to test the association of the app with clinical cognitive and functional tests and investigate the feasibility of at-home testing using AR. We furthermore investigated the test-retest reliability and potential learning effects of the task. The digital score from the AR app could significantly distinguish HC from preclinical AD (preAD) and prodromal AD (proAD), and preAD from proAD, both with in-clinic and at-home tests. For the classification of the proAD group, the digital score (AUC = 0.84 [0.75-0.93], AUC = 0.77 [0.61-0.93]) was as good as the cognitive score (AUC = 0.85 [0.78-0.93]), while for classifying the preAD group, the digital score (AUC = 0.66 [0.53-0.78], AUC = 0.76 [0.61-0.91]) was superior to the cognitive score (AUC = 0.55 [0.42-0.68]). In-clinic and at-home tests moderately correlated (rho = 0.57, p < 0.001). The digital score was associated with the clinical cognitive score (rho = 0.56, p < 0.001). No learning effects were found. Here we report the AR app distinguishes HC from otherwise healthy Aβ-positive individuals, both in the outpatient setting and at home, which is currently not possible with standard cognitive tests.
增强现实(AR)应用程序将虚拟世界与现实世界相结合,能够重现日常生活中的工具性活动(IADL),因此有望在临床和家庭环境中测量早期阿尔茨海默病(AD)患者进行IADL所需的认知能力。本研究的主要目的是使用一款AR应用程序,在早期AD阶段将健康对照(HC)与患有AD病理的参与者区分开来并进行分类。次要目的是测试该应用程序与临床认知和功能测试之间的关联,并研究使用AR进行家庭测试的可行性。我们还研究了该任务的重测信度和潜在的学习效应。AR应用程序的数字评分在临床测试和家庭测试中均能显著区分HC与临床前AD(preAD)和前驱AD(proAD),以及preAD与proAD。对于proAD组的分类,数字评分(AUC = 0.84 [0.75 - 0.93],AUC = 0.77 [0.61 - 0.93])与认知评分(AUC = 0.85 [0.78 - 0.93])相当,而对于preAD组的分类,数字评分(AUC = 0.66 [0.53 - 0.78],AUC = 0.76 [0.61 - 0.91])优于认知评分(AUC = 0.55 [0.42 - 0.68])。临床测试和家庭测试具有中度相关性(rho = 0.57,p < 0.001)。数字评分与临床认知评分相关(rho = 0.56,p < 0.001)。未发现学习效应。在此我们报告,该AR应用程序在门诊环境和家庭中均能将HC与其他健康的Aβ阳性个体区分开来,而这是标准认知测试目前无法做到的。