This paper is in the following e-collection/theme issue:

Development of Novel Medical Devices and Innovations for Existing Devices (107) Mobile Health (mhealth) (3560) New Methods (1152) Digital Biomarkers and Digital Phenotyping (301) Diagnostic Tools in Mental Health (332) Methods and New Tools in Mental Health Research (573)

Published on in Vol 7, No 2 (2022): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41003, first published .
Detection of Mental Fatigue in the General Population: Feasibility Study of Keystroke Dynamics as a Real-world Biomarker

Detection of Mental Fatigue in the General Population: Feasibility Study of Keystroke Dynamics as a Real-world Biomarker

Detection of Mental Fatigue in the General Population: Feasibility Study of Keystroke Dynamics as a Real-world Biomarker

Authors of this article:

Alejandro Acien1, 2 Author Orcid Image ;   Aythami Morales2 Author Orcid Image ;   Ruben Vera-Rodriguez2 Author Orcid Image ;   Julian Fierrez2 Author Orcid Image ;   Ijah Mondesire-Crump1 Author Orcid Image ;   Teresa Arroyo-Gallego1 Author Orcid Image
Article Authors Cited by (12) Tweetations (5) Metrics

Journals

  1. Altwaijry N. Authentication by Keystroke Dynamics: The Influence of Typing Language. Applied Sciences 2023;13(20):11478 View
  2. Liu W, Yeh C, Chen P, Lin C, Liu A. Keystroke Biometrics as a Tool for the Early Diagnosis and Clinical Assessment of Parkinson’s Disease. Diagnostics 2023;13(19):3061 View
  3. Karim E, Pavel H, Nikanfar S, Hebri A, Roy A, Nambiappan H, Jaiswal A, Wylie G, Makedon F. Examining the Landscape of Cognitive Fatigue Detection: A Comprehensive Survey. Technologies 2024;12(3):38 View
  4. Ruiz-Garcia J, Tolosana R, Vera-Rodriguez R, Fierrez J, Herreros-Rodriguez J. ChildCI framework: Analysis of motor and cognitive development in children-computer interaction for age detection. Cognitive Systems Research 2024;86:101230 View
  5. Brinkmann G, Duque-Lopez A, Cui J, Faust L, Alden E, Worrell G, Brinkmann B. Assessing the feasibility of digital keypress statistics to detect seizures and capture cognitive impairment in patients with epilepsy: A pilot study. Epilepsy & Behavior 2024;157:109820 View
  6. Acien A, Morales A, Giancardo L, Vera-Rodriguez R, Holmes A, Fierrez J, Arroyo-Gallego T. KeyGAN: Synthetic keystroke data generation in the context of digital phenotyping. Computers in Biology and Medicine 2025;184:109460 View
  7. Deane P, Zhang M, Hao J, Li C. Using Keystroke Dynamics to Detect Nonoriginal Text. Journal of Educational Measurement 2026;63(1) View
  8. Shadman R, Wahab A, Manno M, Lukaszewski M, Hou D, Hussain F. Keystroke Dynamics: Concepts, Techniques, and Applications. ACM Computing Surveys 2025;57(11):1 View
  9. Bennett D, Roudaut A, Metatla O. Multifractality in typing as a marker of fatigue. International Journal of Human-Computer Studies 2025;204:103595 View
  10. Moon J, Huh Y, Cho H, Kim C, Lee H, Jang D, Cho B. Exploring Age-Related Patterns in Smartphone Keystroke Dynamics Considering Temporal Variability: Cross-Sectional Study With AI-Based Analysis. JMIR mHealth and uHealth 2025;13:e80094 View
  11. Hama Rawf K. Improved CoAtNet for robust acoustic side-channel attack classification on keyboards. International Journal of Information Security 2026;25(1) View

Books/Policy Documents

  1. Macias-Fassio E, Morales A, Pruenza C, Fierrez J. Pattern Recognition. View