Visual and Memory-based HCI Obstacles: Behaviour-based Detection and User Interface Adaptations Analysis

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  • Additional Information
    • Publication Information:
      IEEE
    • Publication Date:
      2019
    • Abstract:
      Human Computer Interaction (HCI) performance can be impaired by several HCI obstacles. Cognitive adaptive systems should dynamically detect such obstacles and compensate them with suitable User Interface (UI) adaptation. In this paper, we discuss the detection of two main HCI obstacles: memory-based and visual obstacles. A sequential model based on Long-Short Term Memory (LSTM) is suggested for such a detection of HCI obstacles. UI adaptations for both types of obstacles are discussed and analyzed. We investigate the classification performance on data from a user study with 17 participants. Furthermore, we also investigate the influence of different adaptation mechanisms on performance and subjective assessment. Results show advantages of the proposed sequential LSTM model: on the one hand, the LSTM outperforms the baseline random guess and also a baseline static model LDA in the detection of visual obstacles with 70.6% as an average accuracy. On the other hand, the evaluation of HCI sessions impeded by obstacles but supported with different UI adaptations shows that LSTM results well match the subjective assessment as a plausible detector of behaviour changes.
    • Contents Note:
      Conference Acronym: SMC
    • Author Affiliations:
      University of Bremen,Cognitive Systems Lab (CSL),Germany
    • ISBN:
      978-1-7281-4569-3
      978-1-7281-4568-6
    • ISSN:
      2577-1655
    • Relation:
      2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
    • Accession Number:
      10.1109/SMC.2019.8914233
    • Rights:
      Copyright 2019, IEEE
    • AMSID:
      8914233
    • Conference Acronym:
      SMC
    • Date of Current Version:
      2019
    • Document Subtype:
      IEEE Conference
    • Notes:
      Conference Location: Bari, Italy, Italy

      Conference Start Date: 6 Oct. 2019

      Conference End Date: 9 Oct. 2019
    • Accession Number:
      edseee.8914233
  • Citations
    • ABNT:
      SALOUS, M. et al. Visual and Memory-based HCI Obstacles: Behaviour-based Detection and User Interface Adaptations Analysis. 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference on, [s. l.], p. 1664–1671, 2019. DOI 10.1109/SMC.2019.8914233. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.8914233. Acesso em: 13 ago. 2020.
    • AMA:
      Salous M, Putze F, Ihrig M, Schultz T. Visual and Memory-based HCI Obstacles: Behaviour-based Detection and User Interface Adaptations Analysis. 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference on. October 2019:1664-1671. doi:10.1109/SMC.2019.8914233
    • APA:
      Salous, M., Putze, F., Ihrig, M., & Schultz, T. (2019). Visual and Memory-based HCI Obstacles: Behaviour-based Detection and User Interface Adaptations Analysis. 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference On, 1664–1671. https://doi.org/10.1109/SMC.2019.8914233
    • Chicago/Turabian: Author-Date:
      Salous, Mazen, Felix Putze, Markus Ihrig, and Tanja Schultz. 2019. “Visual and Memory-Based HCI Obstacles: Behaviour-Based Detection and User Interface Adaptations Analysis.” 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference On, October, 1664–71. doi:10.1109/SMC.2019.8914233.
    • Harvard:
      Salous, M. et al. (2019) ‘Visual and Memory-based HCI Obstacles: Behaviour-based Detection and User Interface Adaptations Analysis’, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference on, pp. 1664–1671. doi: 10.1109/SMC.2019.8914233.
    • Harvard: Australian:
      Salous, M, Putze, F, Ihrig, M & Schultz, T 2019, ‘Visual and Memory-based HCI Obstacles: Behaviour-based Detection and User Interface Adaptations Analysis’, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference on, pp. 1664–1671, viewed 13 August 2020, .
    • MLA:
      Salous, Mazen, et al. “Visual and Memory-Based HCI Obstacles: Behaviour-Based Detection and User Interface Adaptations Analysis.” 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference On, Oct. 2019, pp. 1664–1671. EBSCOhost, doi:10.1109/SMC.2019.8914233.
    • Chicago/Turabian: Humanities:
      Salous, Mazen, Felix Putze, Markus Ihrig, and Tanja Schultz. “Visual and Memory-Based HCI Obstacles: Behaviour-Based Detection and User Interface Adaptations Analysis.” 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference On, October 1, 2019, 1664–71. doi:10.1109/SMC.2019.8914233.
    • Vancouver/ICMJE:
      Salous M, Putze F, Ihrig M, Schultz T. Visual and Memory-based HCI Obstacles: Behaviour-based Detection and User Interface Adaptations Analysis. 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC), Systems, Man and Cybernetics (SMC), 2019 IEEE International Conference on [Internet]. 2019 Oct 1 [cited 2020 Aug 13];1664–71. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.8914233