Large scale mood and stress self-Assessments on a smartwatch

Katrin Hänsel, Akram Alomainy, Hamed Haddadi

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

5 Citations (Scopus)

Abstract

Modern sensing technology is becoming increasingly ubiquitous. Mobile phone sensing data has been used in research to address health and wellbeing; but in the last years, wearable technology became broadly available and popular. This opens new opportunity for health and wellbeing research in the wild. We will present an easy-To-use application to log current emotional states on a widely used smartwatch and collect additional, body sensing data to build a basis for new algorithms, interventions and technologysupported therapy around this data to promote emotional and mental well-being.

Original languageEnglish
Title of host publicationUbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing
PublisherAssociation for Computing Machinery, Inc
Pages1180-1184
Number of pages5
ISBN (Electronic)9781450344623
DOIs
Publication statusPublished - 12 Sep 2016
Externally publishedYes
Event2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016 - Heidelberg, Germany
Duration: 12 Sep 201616 Sep 2016

Other

Other2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016
CountryGermany
CityHeidelberg
Period12/9/1616/9/16

Fingerprint

Health
Mobile phones
Wearable technology

Keywords

  • Affective state
  • Stress
  • Wearable sensing

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Information Systems
  • Computer Networks and Communications
  • Human-Computer Interaction

Cite this

Hänsel, K., Alomainy, A., & Haddadi, H. (2016). Large scale mood and stress self-Assessments on a smartwatch. In UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 1180-1184). Association for Computing Machinery, Inc. https://doi.org/10.1145/2968219.2968305

Large scale mood and stress self-Assessments on a smartwatch. / Hänsel, Katrin; Alomainy, Akram; Haddadi, Hamed.

UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, Inc, 2016. p. 1180-1184.

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

Hänsel, K, Alomainy, A & Haddadi, H 2016, Large scale mood and stress self-Assessments on a smartwatch. in UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, Inc, pp. 1180-1184, 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016, Heidelberg, Germany, 12/9/16. https://doi.org/10.1145/2968219.2968305
Hänsel K, Alomainy A, Haddadi H. Large scale mood and stress self-Assessments on a smartwatch. In UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, Inc. 2016. p. 1180-1184 https://doi.org/10.1145/2968219.2968305
Hänsel, Katrin ; Alomainy, Akram ; Haddadi, Hamed. / Large scale mood and stress self-Assessments on a smartwatch. UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. Association for Computing Machinery, Inc, 2016. pp. 1180-1184
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