Research Article

Estimation of the User’s Emotional State by Keystroke Dynamics

by  Rinky Solanki, Pragya Shukla
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 94 - Issue 13
Published: May 2014
Authors: Rinky Solanki, Pragya Shukla
10.5120/16403-6099
PDF

Rinky Solanki, Pragya Shukla . Estimation of the User’s Emotional State by Keystroke Dynamics. International Journal of Computer Applications. 94, 13 (May 2014), 21-23. DOI=10.5120/16403-6099

                        @article{ 10.5120/16403-6099,
                        author  = { Rinky Solanki,Pragya Shukla },
                        title   = { Estimation of the User’s Emotional State by Keystroke Dynamics },
                        journal = { International Journal of Computer Applications },
                        year    = { 2014 },
                        volume  = { 94 },
                        number  = { 13 },
                        pages   = { 21-23 },
                        doi     = { 10.5120/16403-6099 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2014
                        %A Rinky Solanki
                        %A Pragya Shukla
                        %T Estimation of the User’s Emotional State by Keystroke Dynamics%T 
                        %J International Journal of Computer Applications
                        %V 94
                        %N 13
                        %P 21-23
                        %R 10.5120/16403-6099
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Emotions play a significant role in human computer interaction (HCI). Up to the present, different methods for emotion measurement have been developed like facial expression analysis, voice intonation analysis, thermal imaging etc. Our approach in this paper is to identify users' emotional state based on using standard keyboard. According to the proposed scenarios, emotional states investigated within this research include, but are not limited to, the following ones: confidence, sadness, happiness, tiredness, nervousness, anger.

References
  • Kalakowska A, Zavadskas EK, Seniut M et al (2011), Web-based Biometric Computer Mouse Advisory System to Analyze a User's Emotions and Work Productivity, Engineering Applications of Artificial Intelligence 24: 928-945
  • Maat L, Pantic M (2007), Gaze-X: Adaptive, Affective, Multimodal Interface for Single-User Office Scenarios, Human Computing, LNAI 4451, Springer-Verlag: 251-271
  • Szwoch M (2013), FEEDB: a Multimodal Database of Facial Expressions and Emotions, Proceedings of the 6th International Conference on Human System Interaction, Gdarisk
  • Schuller B, Lang M, Rigoll G (2002), Multimodal emotion recognition in audiovisual communication, Proceedings of IEEE International Conference on Multimedia and Expo, ICME 2002, Lausanne
  • Clayton Epp, Michael Lippold, and Regan L. Mandryk, Identifying Emotional States using Keystroke Dynamics , CHI 2011
  • Zimmermann P, Gomez P, Danuser B, Schar S (2006), Extending usability: putting affect into the user-experience, Proceedings of the 4th Nordic Conf. on Human-Computer Interaction, Oslo, pp 27-32
  • T. Dalgleish. Psychology: An Integrated Approach. by Michael W. Eysenck. Longman, Harlow, 1998.
  • C. Wade and C. Tavris. Psychology. HarperCollins College Publishers, New York, 4 edition, 1996.
  • Lang, P. 1995. The emotion probe. American Psychologist. 50, 5 (1995), 372-385.
  • Carroll, L. Alice's Adventures in Wonderland. The Gutenberg Project, 2008.
  • Althothali A (2011) Modeling user affect using interaction events (thesis), University of Waterloo, Canada
  • Likert R (1932), A technique for the measurement of attitudes, Archives of Psychology, 22(140): 1-55
  • Bradley M, Lang P (1994) Measuring emotion: the self-assessment manikin and the semantic differential. Journal of behavior therapy and experimental psychiatry, 25(1):49-59
  • Lee H, Choi YS, Lee S, Park IP (2012), Towards Unobtrusive Emotion Recognition for Affective Social Communication, Proceedings of the 9th IEEE Consumer Communications and Networking Conference: 260-264
  • Althothali A (2011) Modeling user affect using interaction events (thesis), University of Waterloo, Canada
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Biometrics keystroke dynamics emotion recognition Human computer interaction

Powered by PhDFocusTM