IoT Technologies for HealthCare. 6th EAI International Conference, HealthyIoT 2019, Braga, Portugal, December 4–6, 2019, Proceedings

Research Article

SocialBike: Quantified-Self Data as Social Cue in Physical Activity

  • @INPROCEEDINGS{10.1007/978-3-030-42029-1_7,
        author={Nan Yang and Gerbrand Hout and Loe Feijs and Wei Chen and Jun Hu},
        title={SocialBike: Quantified-Self Data as Social Cue in Physical Activity},
        proceedings={IoT Technologies for HealthCare. 6th EAI International Conference, HealthyIoT 2019, Braga, Portugal, December 4--6, 2019, Proceedings},
        proceedings_a={HEALTHYIOT},
        year={2020},
        month={6},
        keywords={Social interaction Quantified-self Personal informatics Motivation Physical activity Health},
        doi={10.1007/978-3-030-42029-1_7}
    }
    
  • Nan Yang
    Gerbrand Hout
    Loe Feijs
    Wei Chen
    Jun Hu
    Year: 2020
    SocialBike: Quantified-Self Data as Social Cue in Physical Activity
    HEALTHYIOT
    Springer
    DOI: 10.1007/978-3-030-42029-1_7
Nan Yang1,*, Gerbrand Hout2,*, Loe Feijs1,*, Wei Chen3,*, Jun Hu1,*
  • 1: Eindhoven University of Technology
  • 2: Catharina Hospital
  • 3: Fudan University
*Contact email: n.yang@tue.nl, info@drvanhout.nl, l.m.g.feijs@tue.nl, w_chen@fudan.edu.cn, j.hu@tue.nl

Abstract

Quantified-self application is widely used in sports and health management; the type and amount of data that can be fed back to the user are growing rapidly. However, only a few studies discussed the social attributes of quantified-self data, especially in the context of cycling. In this study, we present “SocialBike,” a digital augmented bicycle that aims to increase cyclists’ motivation and social relatedness in physical activity by showing their quantified-self data to each other. To evaluate the concept through a rigorous control experiment, we built a cycling simulation system to simulate a realistic cycling experience with SocialBike. A within-subjects experiment was conducted through the cycling simulation system with 20 participants. Quantitative data were collected with the Intrinsic Motivation Inventory (IMI) and data recorded by the simulation system; qualitative data were collected through user interviews. The result showed that SocialBike increase cyclists’ intrinsic motivation, perceived competence, and social relatedness in physical activity.