Unobtrusive identification of cognitive states for improved knowledge acquisition

Benjamin Tag, Kazunori Sugiura

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

Abstract

One of the major steps in the evolution of Human-computer interaction (HCI) is the introduction of physiological computing. Real-time measurements and analysis of physiological signals through sensors help opening up an implicit communication channel between computers and their users. Awareness of the user's emotional and cognitive states allow computers to react and adapt in real time, and therefore potentially maximize HCI performance efficiency and communication. Ubiquitous wearable computing enables us to make use of computational power in everyday situations. This liberates experiments and applications from necessary heavy stationary devices and controlled laboratory environments. Physiological computing has been used to increase the efficiency of performance, and improve the pleasure derived from interacting with computers. By analyzing physiological data from the user, cognitive states can be monitored and identified [6]. Thereby, the computer becomes aware of the physical, mental, and emotional context of a user. Consequently, the physical data describing negative or positive states can be used as an input modality to dynamically adjust the system, e.g. by altering certain contents, by providing assistance with additional information, turning on/off of certain functions, or triggering a reminder to take a break or walk when sleepiness or frustration result in decreasing attention. These context-aware systems have a proactive nature and therefore omit the necessity for explicit input devices, such as a mouse or a keyboard. They are able to create an interactive loop between a user and a computer. Since the user is constantly processing the information received (e.g. from a watched video), and the ubiquity of mobile devices allows for sensor data to be constantly monitored and processed, we can create biocybernetic loops that are able to respond to desirable and undesirable states [13].

Original languageEnglish
Title of host publicationUbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers
PublisherAssociation for Computing Machinery, Inc
Pages559-564
Number of pages6
ISBN (Electronic)9781450359665
DOIs
Publication statusPublished - 2018 Oct 8
Event2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 - Singapore, Singapore
Duration: 2018 Oct 82018 Oct 12

Other

Other2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018
CountrySingapore
CitySingapore
Period18/10/818/10/12

Fingerprint

Knowledge acquisition
Human computer interaction
Biocybernetics
Sensors
Time measurement
Mobile devices
Communication
Processing
Experiments

Keywords

  • Circadian computing
  • Cognition-aware systems
  • Cognitive load
  • Eye blink
  • Fatigue
  • Thermography
  • Wearable sensors

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Information Systems

Cite this

Tag, B., & Sugiura, K. (2018). Unobtrusive identification of cognitive states for improved knowledge acquisition. In UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers (pp. 559-564). Association for Computing Machinery, Inc. https://doi.org/10.1145/3267305.3267315

Unobtrusive identification of cognitive states for improved knowledge acquisition. / Tag, Benjamin; Sugiura, Kazunori.

UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2018. p. 559-564.

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

Tag, B & Sugiura, K 2018, Unobtrusive identification of cognitive states for improved knowledge acquisition. in UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, pp. 559-564, 2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018, Singapore, Singapore, 18/10/8. https://doi.org/10.1145/3267305.3267315
Tag B, Sugiura K. Unobtrusive identification of cognitive states for improved knowledge acquisition. In UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc. 2018. p. 559-564 https://doi.org/10.1145/3267305.3267315
Tag, Benjamin ; Sugiura, Kazunori. / Unobtrusive identification of cognitive states for improved knowledge acquisition. UbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers. Association for Computing Machinery, Inc, 2018. pp. 559-564
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