Abstract
Currently, there are many software applications to support sports practice and fitness. Although a good number of them provide personalised services to their users, such as training plans adapted to the athlete’s condition, very few of these applications take into account the particular casuistry of women. Moreover, as far as the authors have been able to find, there are no sports applications that take into account the menstrual cycle of women and how this cycle affects them individually. This paper presents a proposal for a telematics platform, SportsWoman, which allows daily recording of information about the menstrual cycle and how it affects the athlete and, based on it, offers personalised recommendations. SportsWoman has been designed as an Expert System based on semantic technologies. In the proposed platform, the knowledge of specialists (physicians and researchers of sports science) is expressed using rules that, in turn, determine the daily recommendations for each user. SportsWoman has been tested and evaluated by 34 athletes through the well-known System Usability Scale, obtaining a value of 86, which corresponds to an acceptable level of usability with a grade B.
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Acknowledgments
This work has been partially funded by the Spanish EAI and ISCIII and the ERDF “A way of making Europe” under projects TIN2016-80515-R (AEI/EFRD, EU) and PI16/00788 (CWB, MABM, LAS, JSV).
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Santos-Gago, J.M. et al. (2019). Towards a Personalised Recommender Platform for Sportswomen. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) New Knowledge in Information Systems and Technologies. WorldCIST'19 2019. Advances in Intelligent Systems and Computing, vol 930. Springer, Cham. https://doi.org/10.1007/978-3-030-16181-1_48
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DOI: https://doi.org/10.1007/978-3-030-16181-1_48
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