Lam, K-H;
Twose, J;
McConchie, H;
Licitra, G;
Meijer, K;
de Ruiter, L;
van Lierop, Z;
... Killestein, J; + view all
(2021)
Smartphone-derived keystroke dynamics are sensitive to relevant changes in multiple sclerosis.
European Journal of Neurology
10.1111/ene.15162.
(In press).
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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 MRI, 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: 94 patients completed the follow-up. The five best performing keystroke features had AUC-values ranging from 0.72 to 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: KD 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.
| Type: | Article |
|---|---|
| Title: | Smartphone-derived keystroke dynamics are sensitive to relevant changes in multiple sclerosis |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/ene.15162 |
| Publisher version: | https://doi.org/10.1111/ene.15162 |
| Language: | English |
| Additional information: | © 2021 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/). |
| Keywords: | Biometry, Multiple Sclerosis, Pattern Recognition, Physiological, ROC Curve, Smartphone |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Brain Repair and Rehabilitation |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10138872 |
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