EasyCog: a fast and effective numerical tool for the self-assessment of cognitive functions

Many pathological conditions, including chronic pain (CP), can impair cognitive functions. These functions are essential for adapting and evolving in concordance with the environment, which are key processes for coping with CP. However, in CP centers, cognitive assessment is rarely included in CP patient follow-up due to a lack of time, appropriate tools, or trained health professionals. To fill this gap, our team developed EasyCog, a digital tool that enables rapid self-assessment of cognitive functions. It enables cognitive evaluation without an experimenter's help, thanks to speech recognition powered by an artificial neural network. In the initial validation steps, we established normative values for 7 cognitive functions on a cohort of 76 healthy subjects. Because EasyCog includes tests comparable to the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE), we assessed its reliability against available normative values. To assess its specificity, we compared data from healthy subjects with 15 subjects with mild cognitive impairment (MCI) and 15 age-matched CP patients selected from a medical center. Finally, we tested EasyCog's test-retest reliability by repeating sessions at different time intervals. EasyCog showed excellent sensitivity to age-related decline, similar to MoCA normative values. Several cognitive functions were significantly and differentially impaired in MCI subjects and CP patients compared to normative values in healthy subjects, confirming good specificity. Finally, test-retest analysis showed no effect at a 4-month interval. In conclusion, EasyCog appears to be a convenient and reliable numeric tool for rapidly assessing and monitoring cognitive functions in patients.