Abstract
Music can have a positive influence on long-distance runners’ motivation and performance. It requires selecting the most suitable music by considering the runner’s physiological data, the type of training session and the geographical and environmental conditions under which the activity is done. In this context, we are interested in studying the runners’ emotions during the training sessions and in using these emotions to recommend personalized music that increases their motivation and performance. More specifically, in this paper we present an adapted glove that integrates different sensors for collecting data, which help to determine the runner’s emotional state, and the changes that it experiences. Preliminary results about the interpretation of these data and emotions are discussed and a prototype of recommendation system based on Spotify is sketched.
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Acknowledgments
This work has been supported by the research project TIN2015-72241-EXP granted by the Spanish Ministerio de Economía y Competitividad.
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Álvarez, P., Beltrán, J.R., Baldassarri, S. (2019). DJ-Running: Wearables and Emotions for Improving Running Performance. In: Ahram, T., Karwowski, W., Taiar, R. (eds) Human Systems Engineering and Design. IHSED 2018. Advances in Intelligent Systems and Computing, vol 876. Springer, Cham. https://doi.org/10.1007/978-3-030-02053-8_128
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DOI: https://doi.org/10.1007/978-3-030-02053-8_128
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