Smart Aging is a Serious games (SGs) platform in a 3D virtual environment in which users perform a set of screening tests that address various cognitive skills. The tests are structured as 5 tasks of activities of daily life in a familiar environment. The main goal of the present study is to compare a cognitive evaluation made with Smart Aging with those of a classic standardized screening test, the Montreal Cognitive Assessment (MoCA). One thousand one-hundred thirty-one healthy adults aged between 50 and 80 ( = 64.3 ± 8.3) were enrolled in the study. They received a cognitive evaluation with the MoCA and the Smart Aging platform. Participants were grouped according to their MoCA global and specific cognitive domain (i.e., memory, executive functions, working memory, visual spatial elaboration, language, and orientation) scores and we explored differences among these groups in the Smart Aging indices. One thousand eighty-six older adults ( = 64.0 ± 8.0) successfully completed the study and were stratified according to their MoCA score: Group 1 with MoCA < 27 ( = 360); Group 2 with 27 ≥ MoCA < 29 ( = 453); and Group 3 with MoCA ≥ 29 ( = 273). MoCA groups significantly differed in most of the Smart Aging indices considered, in particular as concerns accuracy (s < 0.001) and time (s < 0.001) for completing most of the platform tasks. Group 1 was outperformed by the other two Groups and was slower than them in these tasks, which were those supposed to assess memory and executive functions. In addition, significant differences across groups also emerged when considering the single cognitive domains of the MoCA and the corresponding performances in each Smart Aging task. In particular, this platform seems to be a good proxy for assessing memory, executive functions, working memory, and visual spatial processes. These findings demonstrate the validity of Smart Aging for assessing cognitive functions in normal aging. Future studies will validate this platform also in the clinical aging populations.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5702318PMC
http://dx.doi.org/10.3389/fnagi.2017.00379DOI Listing

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