Education may play a key role in developing 'cognitive reserve' against neurodegenerative dementia. In this work, we investigate for the first time if handwriting dynamics can serve as a quantitative indicator of this reserve. We carried out an exploratory study involving a sample of mild cognitive impairment (MCI) subjects, with high and low education respectively, and a sample of healthy elder controls. We asked them to perform three complex handwriting tasks on a digitizing tablet: Drawing a clock; copying a check; writing a spontaneous sentence. Dynamic measures of the handwriting were then analyzed both with an unsupervised and a supervised machine learning approach. The results we obtained suggest that: (i) handwriting of MCI subjects with high reserve is quite similar to that of controls; (ii) handwriting of MCI subjects with lower reserve is easier to be distinguished from the other two. Dynamic handwriting analysis could provide a novel methodology to elucidate the still unknown mechanisms underlying brain resilience.
|Nome||CONFERENCE PROCEEDINGS / IEEE INTERNATIONAL CONFERENCE ON SYSTEMS MAN AND CYBERNETICS|
|Convegno||2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019|
|Periodo||6/10/19 → 9/10/19|
- Education, Task analysis, Writing, Clocks, Principal component analysis, Dementia, Acceleration