Affiliations: [a] 3rd Department of Neurology, Aristotle University of Thessaloniki, Greece
| [b] Network Aging Research, University of Heidelberg, Germany
| [c]
Cannot Not Design + (CND+) Design Research Organization, Thessaloniki, Greece
| [d] Greek Association of Alzheimer’s Disease and Related Disorders, Thessaloniki, Greece
| [e] Information Technologies Institute, The Centre for Research and Technology Hellas, Thessaloniki, Greece
| [f] Department of Special Education, University of Thessaly, Greece
Correspondence:
[*]
Correspondence to: Stelios Zygouris, MSc, 3rd Department of Neurology, Aristotle, University of Thessaloniki, Sevillis 6, 54633 Thessaloniki, Greece. Tel.: +30 2310 268 471; Fax: +30 2310 351 456; E-mail: [email protected].
Abstract: Background: It has been demonstrated that virtual reality (VR) applications can be used for the detection of mild cognitive impairment (MCI). Objective: The aim of this study is to provide a preliminary investigation on whether a VR cognitive training application can be used to detect MCI in persons using the application at home without the help of an examiner. Methods: Two groups, one of healthy older adults (n = 6) and one of MCI patients (n = 6) were recruited from Thessaloniki day centers for cognitive disorders and provided with a tablet PC with custom software enabling the self-administration of the Virtual Super Market (VSM) cognitive training exercise. The average performance (from 20 administrations of the exercise) of the two groups was compared and was also correlated with performance in established neuropsychological tests. Results: Average performance in terms of duration to complete the given exercise differed significantly between healthy(μ = 247.41 s/ sd = 89.006) and MCI (μ= 454.52 s/ sd = 177.604) groups, yielding a correct classification rate of 91.8% with a sensitivity and specificity of 94% and 89% respectively for MCI detection. Average performance also correlated significantly with performance in Functional Cognitive Assessment Scale (FUCAS), Test of Everyday Attention (TEA), and Rey Osterrieth Complex Figure test (ROCFT). Discussion: The VR application exhibited very high accuracy in detecting MCI while all participants were able to operate the tablet and application on their own. Diagnostic accuracy was improved compared to a previous study using data from only one administration of the exercise. The results of the present study suggest that remote MCI detection through VR applications can be feasible.
Keywords: Aging, Alzheimer’s disease, computers, dementia, diagnosis, memory disorders, mild cognitive impairment, new technologies, practice effect, tablet PC
