**6. Conclusions**

In this work, a personalized intensity level system for the users of assisted electric bicycles has been designed and implemented. The designed system establishes different assist levels in a personalized way, considering the profile of the route, the power required and the user's ability level. As the user travels new routes, the system awards them with higher scores. The higher the score, the greater the average speed on the routes cycled by the user and the greater the amount of power that the user needs to generate. Thanks to the progressive increase in speed, the user gradually does more physical exercise, improving and increasing their fitness. Therefore, it is possible to replace the gym with the use of the electric bicycle for daily commutes saving economic and time costs. This is an important finding of this work.

The innovative component presented in this work is the personalized calculation of exercise for electric bicycle users. Thanks to this system, the user will be able to cycle the routes according to their physical state and ability level. As the user moves up the designed ability levels, the cycling difficulty increases. As demonstrated in Section 5.1, where a route cycled by one of the users has been analyzed, the performance of the designed system is satisfactory. It can segment the route according to its slopes and establish the power that is to be provided by the user, according to its characteristics. The proposed system also evaluates the data collected along the route that had been cycled. This study also demonstrated that the amount of hours the nine case study participants spent on physical activities in a week increased over the four months. This improvement was achieved for both users who were physically fit and those that were not. In general, all users said they were satisfied with their results upon the completion of the 16 weeks of testing. The users whose previous average activity was low (between 0 and 2 h a week) reported that the combination of the e-bike and the training module had helped them increase the amount if exercise they did weekly. The users who were used to regular exercise said that the scoring system and social competition had motivated them to further increase the number of hours they dedicated to exercise weekly.

Thanks to the novel system with assist levels, the more advanced users could progress quickly while the users who were less prepared made a gradual and constant improvement over the four months. The case study participants were located in four different cities, in three different European countries. In future work, a case study will be conducted with users from different parts of the world, whose areas will be more heterogeneous. In the future, we would also like to validate the feasibility of the system in terms of its suitability for people of different ages. To this end, we will conduct a case study that will divide participants into different age groups, such as young people, adults and the elderly.

**Acknowledgments:** This work has been supported by project GatEBike: Arquitectura basada en Computación Social para el control Inteligente e Interacción en Bicicletas Eléctricas. RTC-2015-4171-4. Project co-financed with Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional (FEDER) funds (RETOS-COLABORACIÓN 2015). The research of Alberto López Barriuso has been co-financed by the European Social Fund and Junta de Castilla y León (Operational Programme 2014–2020 for Castilla y León, EDU/128/2015 BOCYL).

**Author Contributions:** Daniel Hernández de la Iglesia and Juan F. De Paz developed the system, performed the test and elaborated the review of the state of the art. Javier Bajo, Alberto López Barriuso, Juan M. Corchado and Gabriel Villarrubia formalized the problem, wrote the algorithms and reviewed the work. All authors contributed to the revision of the paper.

**Conflicts of Interest:** The authors declare no conflict of interest.
