Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Mediation Analysis Between Brain Age, Disease-Modifying Factors, and Disability and Cognitive Performance in Multiple Sclerosis.

Neurology·2026
Same author

The practice effect of smartphone-derived cognitive processing speed assessments as a proxy of cognitive functioning in multiple sclerosis.

Journal of neurology·2026
Same author

Multiple Sclerosis-Specific Reference Curves for Brain Volumes to Explain Disease Severity.

Neurology·2026
Same author

Association of Brain Age With Physical Disability and Cognitive Impairment in People With Multiple Sclerosis of the Same Age.

Neurology·2025
Same author

Feasibility of Simon Two-Stage Futility Trials in People with Early, Symptomatically Treated Parkinson's Disease.

Movement disorders : official journal of the Movement Disorder Society·2025
Same author

Cognitive test performance and disease progression in primary and secondary progressive MS: An analysis of the SPRINT-MS study.

Multiple sclerosis (Houndmills, Basingstoke, England)·2025
Same journal

Individual Variability of CD19+ B-Cell Repopulation in People With Multiple Sclerosis Treated With Extended Interval Dosing of Ocrelizumab.

European journal of neurology·2026
Same journal

Correction to 'Pharmacological Interventions for Hereditary Transthyretin-Related Amyloidosis With Polyneuropathy: Systematic Review and Network Meta-Analysis'.

European journal of neurology·2026
Same journal

Diagnostic Value of Neurofilament Light Chain and Glial Fibrillary Acidic Protein in Differentiating Primary From Serious Secondary Headache.

European journal of neurology·2026
Same journal

Neuropsychiatric Adverse Events Associated With Foslevodopa/Foscarbidopa Continuous Subcutaneous Infusion in Clinical Practice: A Multicenter Study.

European journal of neurology·2026
Same journal

Transfusion-Associated Graft-Versus-Host Disease Risk and Transfusion Requirements After Cladribine in Multiple Sclerosis: Time to Revise Irradiation Policy?

European journal of neurology·2026
Same journal

Blood Pressure Control With Clevidipine Is Associated With Hematoma Volume Reduction in Acute Hypertensive Intracerebral Hemorrhage: A Single-Center Prospective Cohort Study.

European journal of neurology·2026
See all related articles

Related Experiment Video

Updated: Oct 15, 2025

An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones
05:42

An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones

Published on: October 5, 2020

3.3K

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

Ka-Hoo Lam1, James Twose2, Hannah McConchie2

  • 1Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

European Journal of Neurology
|October 31, 2021
PubMed
Summary
This summary is machine-generated.

Smartphone typing patterns, or keystroke dynamics (KD), effectively track changes in multiple sclerosis (MS) disease activity and disability. This digital biomarker shows greater responsiveness than traditional clinical measures for MS.

Keywords:
ROC curvebiometrymultiple sclerosispattern recognitionphysiologicalsmartphone

More Related Videos

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool
11:35

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

Published on: June 30, 2014

58.2K
Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment
05:58

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

Published on: March 11, 2021

4.7K

Related Experiment Videos

Last Updated: Oct 15, 2025

An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones
05:42

An Assessment Method and Toolkit to Evaluate Keyboard Design on Smartphones

Published on: October 5, 2020

3.3K
The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool
11:35

The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool

Published on: June 30, 2014

58.2K
Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment
05:58

Digital Handwriting Analysis of Characters in Chinese Patients with Mild Cognitive Impairment

Published on: March 11, 2021

4.7K

Area of Science:

  • Neurology
  • Digital Health
  • Biomarkers

Background:

  • Multiple Sclerosis (MS) presents challenges in monitoring disease progression and patient-reported outcomes.
  • Objective and sensitive methods are needed to track changes in MS disease activity, fatigue, and disability.

Purpose of the Study:

  • To evaluate the sensitivity of smartphone keystroke dynamics (KD) to changes in multiple sclerosis (MS) disease activity, fatigue, and clinical disability.
  • To compare the responsiveness of KD to established clinical measures in MS patients.

Main Methods:

  • A cohort study involving 102 MS patients assessed over 3 months.
  • Keystroke data collected unobtrusively via the Neurokeys App, with 15 features extracted.
  • Responsiveness assessed using Area Under the Receiver Operating Characteristic Curve (AUC), Minimal Clinically Important Difference (MCID), and Smallest Real Change (SRC).

Main Results:

  • Five key keystroke features demonstrated strong AUC values (0.66-0.79) for tracking changes in MS disease activity, fatigue, and disability.
  • The MCID for these KD features surpassed the SRC at a group level.
  • KD showed higher responsiveness than most common clinical measures, except for ambulatory function.

Conclusions:

  • Keystroke dynamics are a responsive digital biomarker for detecting meaningful changes in MS.
  • KD offers a sensitive, objective method for monitoring disease activity, fatigue, and disability in MS patients.
  • The findings suggest KD can provide valuable insights beyond traditional clinical assessments in MS.