Mobile Computing, Applications, and Services. 10th EAI International Conference, MobiCASE 2019, Hangzhou, China, June 14–15, 2019, Proceedings

Research Article

Would I Lie to You - Would You Notice?

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  • @INPROCEEDINGS{10.1007/978-3-030-28468-8_17,
        author={Felix Huppert and Matthias Kranz and Gerold Hoelzl},
        title={Would I Lie to You - Would You Notice?},
        proceedings={Mobile Computing, Applications, and Services. 10th EAI International Conference, MobiCASE 2019, Hangzhou, China, June 14--15, 2019, Proceedings},
        proceedings_a={MOBICASE},
        year={2019},
        month={9},
        keywords={Fitness tracking User perceived credibility Quantified self Trust in data},
        doi={10.1007/978-3-030-28468-8_17}
    }
    
  • Felix Huppert
    Matthias Kranz
    Gerold Hoelzl
    Year: 2019
    Would I Lie to You - Would You Notice?
    MOBICASE
    Springer
    DOI: 10.1007/978-3-030-28468-8_17
Felix Huppert1,*, Matthias Kranz1,*, Gerold Hoelzl1,*
  • 1: University of Passau
*Contact email: felix.huppert@uni-passau.de, matthias.kranz@uni-passau.de, gerold.hoelzl@uni-passau.de

Abstract

The quantified self-paradigm is well established. Its main purpose is to use numbers from sensors to derive self-knowledge. The massive availability of persuasive technology to monitor physiological parameters of humans made the paradigm available to a tremendous number of people. A multitude of different hard- and software platforms are available at the market. They all have different properties at different levels of quality. All in common is their promise to provide accurate and precise data about the humans’ physiological condition and performed activities. Basically, they all provide a tool to make people aware of formerly hidden, non-observable, body signals. The gained awareness can then be used by people to e.g. improve their health or fitness level. In this work, we emphasize the perception of the gathered sensory data by the people. We focus on the question of how the trustworthiness of the recorded and presented data is perceived by people. As a fact, non-credible data can be understood by the user as being trustworthy and can have a negative impact on users’ behavior. This can be especially critical for human’s health in the fitness and medical application domain. It is of high importance to understand how people perceive and correlate their intrinsic body feelings with the data collected and presented by a mobile smart device like a smart watch or a fitness tracker.