To assist monitoring and screening, digital biomarkers derived from commercial off-the-shelf video games may be of interest. However, this condition is underdiagnosed.
Mild cognitive impairment (MCI), the intermediate cognitive status between normal cognitive decline and pathological decline, is an important clinical construct for signaling possible prodromes of dementia. Nevertheless, as this is a first, exploratory study, further research is necessary. To conclude, this study suggests that commercial off-the-shelf games hold promise for the acquisition of digital biomarkers on cognitive aging and provides benchmark data for future studies.
However, classifying middle-aged players remains problematic. Performance metrics suggest that our model is successful in classifying young and older participants. We found features retained for the model to support theories on fluid intelligence and cognitive functions sensitive to cognitive aging. Next, features were engineered and a machine learning model (Logistic Regression) was trained. To this end, candidates for digital biomarkers of cognitive performance were captured via FreeCell, from three distinctive age groups (18-25, 40-55, 65+) from 52 participants, playing for a total of 130 game rounds. We report on an exploratory study for assessing cognitive aging based on the acquisition and modeling of player data of commercial off-the-shelf games.
0 kommentar(er)
