Cognitive aid: task assistance based on mental workload estimation

Qiushi Zhou, Namrata Srivastava, Jorge Goncalves, Joshua Newn, Tilman Dingler, Eduardo Velloso

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

4 Citations (Scopus)

Abstract

In this work, we evaluate the potential of using wearable non-contact (infrared) thermal sensors through a user study (N=12) to measure mental workload. Our results indicate the possibility of mental workload estimation through the temperature changes detected using the prototype as participants perform two task variants with increasing difficulty levels. While the sensor accuracy and the design of the prototype can be further improved, the prototype showed the potential of building AR-based systems with cognitive aid technology for ubiquitous task assistance from the changes in mental workload demands. As such, we demonstrate our next steps by integrating our prototype into an existing AR headset (i.e. Microsoft HoloLens).

Original languageEnglish
Title of host publicationExtended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems
EditorsAnna Cox, Vassilis Kostakos
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Number of pages6
ISBN (Electronic)9781450359719
DOIs
Publication statusPublished - 2019
Externally publishedYes
EventInternational Conference on Human Factors in Computing Systems 2019 - Glasgow, United Kingdom
Duration: 4 May 20199 May 2019
Conference number: 37th
https://chi2019.acm.org
https://dl.acm.org/doi/proceedings/10.1145/3290605 (Proceedings)

Conference

ConferenceInternational Conference on Human Factors in Computing Systems 2019
Abbreviated titleCHI 2019
CountryUnited Kingdom
CityGlasgow
Period4/05/199/05/19
Internet address

Keywords

  • Affective computing
  • Cognitive load
  • Thermal sensor

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