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Detecting Flow Experiences in the Field Using Video-Based Head and Face Activity Recognition: A Pilot Study

In: Information Systems and Neuroscience

Author

Listed:
  • Christoph Berger

    (Karlsruhe Institute of Technology (KIT))

  • Michael T. Knierim

    (Karlsruhe Institute of Technology (KIT))

  • Christof Weinhardt

    (Karlsruhe Institute of Technology (KIT))

Abstract

Flow represents a valuable daily life experience as it is linked to performance, growth, and well-being. As flow support is still a major challenge due to a lack of automatic and unobtrusive detection methods, NeuroIS scholars face the opportunity to devise measurement approaches for flow experience during IS use and, moreover, flow supporting, adaptive NeuroIS. This work presents the first results from a controlled experience sampling field study in which experiences were observed using video recordings during a week of scientific writing. Novel behavioral features (face and head activity) with negative flow-report correlations are identified. Together, the results contribute to the NeuroIS community by providing an extended concept of flow as a state of behavioral efficiency, the identification of novel correlates, and recommendations for economical and feasible extensions of the study approach.

Suggested Citation

  • Christoph Berger & Michael T. Knierim & Christof Weinhardt, 2021. "Detecting Flow Experiences in the Field Using Video-Based Head and Face Activity Recognition: A Pilot Study," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph & Gernot (ed.), Information Systems and Neuroscience, pages 120-127, Springer.
    • Handle: RePEc:spr:lnichp:978-3-030-88900-5_14
    DOI: 10.1007/978-3-030-88900-5_14
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