Keep the Beat: Audio Guidance for Runner Training

  • Luca Balvis
  • Ludovico Boratto
  • Fabrizio Mulas
  • Lucio Davide Spano
  • Salvatore Carta
  • Gianni Fenu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9856)


Understanding how to map the feedback by fitness apps into concrete actions during the exercise performance is crucial for their effectiveness, for both inexperienced and advanced users. In this paper we focus on audio feedback for running, describing a beat-rhythm representation of the target cadence for helping the user in keeping it. We designed the feedback system in order to balance two conflicting objectives: its effectiveness in helping the user in reaching the training goal and its intrusiveness with respect to concurrent activities (e.g., listening to the music). We detail how we track the user’s cadence through standard smartphone sensors, how and when we generate the audio messages. Finally, we discuss the results of a user-study, showing effectiveness with respect to the adherence to the exercise goal and the overall usability.


Audio guidance Beats Running Training Evaluation Fitness 


  1. 1.
    Consolvo, S., McDonald, D.W., Toscos, T., Chen, M.Y., Froehlich, J., Harrison, B., Klasnja, P., LaMarca, A., LeGrand, L., Libby, R., Smith, I., Landay, J.A.: Activity sensing in the wild: a field trial of ubifit garden. In: Proceedings of CHI 2008, pp. 1797–1806. ACM (2008).
  2. 2.
    De Oliveira, R., Oliver, N.: Triplebeat: enhancing exercise performance with persuasion. In: Proceedings of MobileHCI 2008, pp. 255–264. ACM (2008).
  3. 3.
    Fortmann, J., Pielot, M., Mittelsdorf, M., Büscher, M., Trienen, S., Boll, S.: Paceguard: improving running cadence by real-time auditory feedback. In: Proceedings of MobileHCI 2012, pp. 5–10. ACM (2012).
  4. 4.
    Jayalath, S., Abhayasinghe, N.: A gyroscopic data based pedometer algorithm. In: Proceedings of ICCSE 2013, pp. 551–555 (2013)Google Scholar
  5. 5.
    Moens, B., Muller, C., van Noorden, L., Franěk, M., Celie, B., Boone, J., Bourgois, J., Leman, M.: Encouraging spontaneous synchronisation with d-jogger, an adaptive music player that aligns movement and music. PloS One 9(12), e114234 (2014)Google Scholar
  6. 6.
    Mulas, F., Carta, S., Pilloni, P., Manca, M.: Everywhere run: a virtual personal trainer for supporting people in their running activity. In: Proceedings of ACE 2011, pp. 70:1–70:2. ACM (2011)Google Scholar
  7. 7.
    Nylander, S., Jacobsson, M., Tholander, J.: Runright: real-time visual and audio feedback on running. In: CHI 2014 Extended Abstracts, CHI EA 2014, pp. 583–586. ACM (2014).
  8. 8.
    Nylander, S., Kent, A., Tholander, J.: Swing sound: experiencing the golf swing through sound. In: CHI 2014 Extended Abstracts, pp. 443–446. ACM (2014).
  9. 9.
    Oliver, N., Flores-Mangas, F.: Mptrain: a mobile, music and physiology-based personal trainer. In: Proceedings of MobileHCI 2006, pp. 21–28. ACM (2006).
  10. 10.
    Stienstra, J., Overbeeke, K., Wensveen, S.: Embodying complexity through movement sonification: case study on empowering the speed-skater. In: Proceedings of CHItaly 2011, pp. 39–44. ACM (2011).
  11. 11.
    Terry, P.C., Karageorghis, C.I., Saha, A.M., D’Auria, S.: Effects of synchronous music on treadmill running among elite triathletes. J. Sci. Med. Sport 15(1), 52–57 (2012)CrossRefGoogle Scholar
  12. 12.
    Tomlein, M., Bielik, P., Krtky, P., tefan Mitrk, Barla, M., Bielikov, M.: Advanced pedometer for smartphone-based activity tracking. In: Proceedings of BIOSTEC 2012, pp. 401–404 (2012)Google Scholar
  13. 13.
    Waterhouse, J., Hudson, P., Edwards, B.: Effects of music tempo upon submaximal cycling performance. Scand. J. Med. Sci. Sports 20(4), 662–669 (2010)CrossRefGoogle Scholar
  14. 14.
    Woźniak, P., Knaving, K., Björk, S., Fjeld, M.: Rufus: remote supporter feedback for long-distance runners. In: Proceedings of MobileHCI 2015, pp. 115–124. ACM (2015).
  15. 15.
    Zhao, S., Dragicevic, P., Chignell, M., Balakrishnan, R., Baudisch, P.: Earpod: eyes-free menu selection using touch input and reactive audio feedback. In: Proceedings of CHI 2007, pp. 1395–1404. ACM (2007).

Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  • Luca Balvis
    • 1
  • Ludovico Boratto
    • 1
  • Fabrizio Mulas
    • 1
  • Lucio Davide Spano
    • 1
  • Salvatore Carta
    • 1
  • Gianni Fenu
    • 1
  1. 1.Department of Mathematics and Computer ScienceUniversity of CagliariCagliariItaly

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