Associations between smartphone keystroke dynamics and cognition in MS

Michelle H Chen; Alex Leow; Mindy K Ross; John DeLuca; Nancy Chiaravalloti; Silvana L Costa; Helen M Genova; Erica Weber; Faraz Hussain; Alexander P Demos

doi:10.1177/20552076221143234

Associations between smartphone keystroke dynamics and cognition in MS

Digit Health. 2022 Dec 5:8:20552076221143234. doi: 10.1177/20552076221143234. eCollection 2022 Jan-Dec.

Authors

Michelle H Chen^{1

2}, Alex Leow³, Mindy K Ross³, John DeLuca^{4

5}, Nancy Chiaravalloti^{4

5}, Silvana L Costa^{4

5}, Helen M Genova^{4

5}, Erica Weber^{4

5}, Faraz Hussain³, Alexander P Demos³

Affiliations

¹ Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, USA.
² Department of Neurology, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA.
³ Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA.
⁴ Kessler Foundation, East Hanover, NJ, USA.
⁵ Department of Physical Medicine and Rehabilitation, New Jersey Medical School, Rutgers University, Newark, NJ, USA.

Abstract

Objective: Examine the associations between smartphone keystroke dynamics and cognitive functioning among persons with multiple sclerosis (MS).

Methods: Sixteen persons with MS with no self-reported upper extremity or typing difficulties and 10 healthy controls (HCs) completed six weeks of remote monitoring of their keystroke dynamics (i.e., how they typed on their smartphone keyboards). They also completed a comprehensive neuropsychological assessment and symptom ratings about fatigue, depression, and anxiety at baseline.

Results: A total of 1,335,787 keystrokes were collected, which were part of 30,968 typing sessions. The MS group typed slower (P < .001) and more variably (P = .032) than the HC group. Faster typing speed was associated with better performance on measures of processing speed (P = .016), attention (P = .022), and executive functioning (cognitive flexibility: P = .029; behavioral inhibition: P = .002; verbal fluency: P = .039), as well as less severe impact from fatigue (P < .001) and less severe anxiety symptoms (P = .007). Those with better cognitive functioning and less severe symptoms showed a stronger correlation between the use of backspace and autocorrection events (P < .001).

Conclusion: Typing speed may be sensitive to cognitive functions subserved by the frontal-subcortical brain circuits. Individuals with better cognitive functioning and less severe symptoms may be better at monitoring their typing errors. Keystroke dynamics have the potential to be used as an unobtrusive remote monitoring method for real-life cognitive functioning among persons with MS, which may improve the detection of relapses, evaluate treatment efficacy, and track disability progression.

Keywords: Multiple sclerosis; digital phenotyping; mHealth; passive monitoring; typing.