Detecting cognitive impairment using keystroke and linguistic features of typed text: Toward an adaptive method for continuous monitoring of cognitive status

Lisa M. Vizer, Andrew L. Sears

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Perception, attention, and memory form the foundation of human cognition, and are functions that most people take for granted. However, factors such as environment, mood, stress, education, trauma, aging, or disease can impact cognitive function both positively and negatively. For example, working memory capacity generally declines somewhat with age, but a particular individual's accumulated knowledge and skills usually remain intact and can continue to grow. Current methods of monitoring persons for cognitive decline use only normative data and do not take individual differences into account. Given that early intervention can lessen the impact of cognitive decline, concern that current cognitive assessments do not adequately address individual differences, and growing technology use by older adults, this paper investigates a more effective method for monitoring cognitive function using everyday interactions with IT.

Original languageEnglish (US)
Title of host publicationInformation Quality in e-Health - 7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011, Proceedings
Pages483-500
Number of pages18
DOIs
StatePublished - Nov 30 2011
Event7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011 - Graz, Austria
Duration: Nov 25 2011Nov 26 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7058 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011
CountryAustria
CityGraz
Period11/25/1111/26/11

Fingerprint

Adaptive Method
Linguistics
Individual Differences
Monitoring
Data storage equipment
Working Memory
Mood
Cognition
Person
Continue
Aging of materials
Education
Interaction
Text

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Vizer, L. M., & Sears, A. L. (2011). Detecting cognitive impairment using keystroke and linguistic features of typed text: Toward an adaptive method for continuous monitoring of cognitive status. In Information Quality in e-Health - 7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011, Proceedings (pp. 483-500). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7058 LNCS). https://doi.org/10.1007/978-3-642-25364-5_34
Vizer, Lisa M. ; Sears, Andrew L. / Detecting cognitive impairment using keystroke and linguistic features of typed text : Toward an adaptive method for continuous monitoring of cognitive status. Information Quality in e-Health - 7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011, Proceedings. 2011. pp. 483-500 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Vizer, LM & Sears, AL 2011, Detecting cognitive impairment using keystroke and linguistic features of typed text: Toward an adaptive method for continuous monitoring of cognitive status. in Information Quality in e-Health - 7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7058 LNCS, pp. 483-500, 7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011, Graz, Austria, 11/25/11. https://doi.org/10.1007/978-3-642-25364-5_34

Detecting cognitive impairment using keystroke and linguistic features of typed text : Toward an adaptive method for continuous monitoring of cognitive status. / Vizer, Lisa M.; Sears, Andrew L.

Information Quality in e-Health - 7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011, Proceedings. 2011. p. 483-500 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7058 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Vizer LM, Sears AL. Detecting cognitive impairment using keystroke and linguistic features of typed text: Toward an adaptive method for continuous monitoring of cognitive status. In Information Quality in e-Health - 7th Conference of the Workgroup Human-Computer Interaction and Usability Engineering of the Austrian Computer Society, USAB 2011, Proceedings. 2011. p. 483-500. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-25364-5_34