Smartphone‐derived keystroke dynamics are sensitive to relevant changes in multiple sclerosis

Abstract

Background To investigate smartphone keystroke dynamics (KD), derived from regular typing, on sensitivity to relevant change in disease activity, fatigue, and clinical disability in multiple sclerosis (MS). Methods Preplanned interim analysis of a cohort study with 102 MS patients assessed at baseline and 3‐month follow‐up for gadolinium‐enhancing lesions on magnetic resonance imaging, relapses, fatigue and clinical disability outcomes. Keyboard interactions were unobtrusively collected during typing using the Neurokeys App. From these interactions 15 keystroke features were derived and aggregated using 16 summary and time series statistics. Responsiveness of KD to clinical anchor‐based change was assessed by calculating the area under the receiver operating characteristic curve (AUC). The optimal cut‐point was used to determine the minimal clinically important difference (MCID) and compared to the smallest real change (SRC). Commonly used clinical measures were analyzed for comparison. Results A total of 94 patients completed the follow‐up. The five best performing keystroke features had AUC‐values in the range 0.72–0.78 for change in gadolinium‐enhancing lesions, 0.67–0.70 for the Checklist Individual Strength Fatigue subscale, 0.66–0.79 for the Expanded Disability Status Scale, 0.69–0.73 for the Ambulation Functional System, and 0.72–0.75 for Arm function in MS Questionnaire. The MCID of these features exceeded the SRC on group level. KD had higher AUC‐values than comparative clinical measures for the study outcomes, aside from ambulatory function. Conclusions Keystroke dynamics demonstrated good responsiveness to changes in disease activity, fatigue, and clinical disability in MS, and detected important change beyond measurement error on group level. Responsiveness of KD was better than commonly used clinical measures.

The Use of Smartphone Keystroke Dynamics to Passively Monitor Upper Limb and Cognitive Function in Multiple Sclerosis: Longitudinal Analysis

“…Despite this, the use of KD in the assessment of diseases is relatively underutilized, especially considering that touchscreen typing has existed for over a decade. Hence, our objective was to validate the use of passive KD, measured with the Neurokeys app, to improve disease management in MS. To this end, earlier investigations by our research group reported on the clinimetric properties of reliability, validity, and 3-month responsiveness of KD in MS [ 10 , 11 ]. To the best of our knowledge, other applications of KD analysis in diseases are limited to the detection of early-stage Parkinson disease [ 23 - 28 ], upper limb dysfunction in amyotrophic lateral sclerosis [ 29 ], and severity in mood disorders [ 30 , 31 ].…”

“…This was a prospective cohort study at the MS Center of the Amsterdam University Medical Centers (VU University Medical Center location). The study design and interim analyses have been reported previously [ 10 , 11 ]. In brief, after a baseline assessment (M 0 ), we followed the patients for 1 year, with clinical visits every 3 months (M 3 , M 6 , M 9 , and M 12 ).…”

“…In our previous work, KD was found to be correlated with upper limb and cognitive function, and, to a lesser extent, overall disability, as measured with the EDSS [ 10 ]. Across a wide range of KD features and aggregation methods, KD was also found to reach adequate responsiveness to meaningful change in radiological disease activity, ambulatory function, and upper limb function over a period of 3 months [ 11 ]. Additionally, analysis of KD data using a nonlinear time-series approach identified potential indicators of clinical change [ 12 ].…”

Associations between smartphone keystroke dynamics and cognition in MS

“… 12 , 13 In MS, keystroke dynamics have been linked with performances on motor and cognitive tests, brain lesions, and neurological disability. 14 , 15 …”

“…Existing keystroke studies in MS have only used a brief cognitive screener measuring processing speed. 14 , 15 Studies in populations with cognitive impairment as a primary feature (e.g., mild cognitive impairment and dementia) focus on classification between clinical and control groups 16 , 17 ; thus, associations between keystroke features and specific cognitive domains remain unknown. The goal of the current study was to provide proof-of-concept evidence that keystroke dynamics have the potential to be used as an unobtrusive remote monitoring method for real-life cognitive functioning.…”