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- Supporting Students' Mental Health and Academic Success Through Mobile App and IoTPublication . Baras, Karolina; Soares, Luísa; Lucas, Carla Vale; Oliveira, Filipa; Paulo, Norberto Pinto; Barros, ReginaSmartphones have become devices of choice for running studies on health and well-being, especially among young people. When entering college,students often face many challenges,such as adaptation to new situations, establish new interpersonal relationships, heavier workload and shorter deadlines, teamwork assignments and others. In this paper, the results of four studies examining students’ well being and mental health as well as student’s perception of challenges and obstacles they face during their academic journey are presented. In addition, a mobile application that acts as a complement to a successful tutoring project implemented at the authors’ University is proposed. The application allows students to keep their schedules and deadlines in one place while incorporating virtual tutor features. By using both, the events from the student’s calendar and his or her mood indicators, the application sends notifications accordingly. These notifications encompass motivational phrases, time management guidelines, as well as relaxation tips.
- Overview of context-sensitive technologies for well-beingPublication . Freitas, André; Brito, Lina; Baras, Karolina; Silva, JoséToday smart devices such as smartphones, smartwatches and activity trackers are widely available and accepted in most developed societies. These devices present a broad set of sensors capable of extracting detailed information about different situations of daily life, which, if used for good, have the potential to improve the quality of life not only for individuals but also for the society in general. One of the key areas where this type of information can help to improve the quality of life is in healthcare since it allows to monitor and infer the current level of well-being of the smart devices carriers. In this paper, some of the available literature about well-being sensing through context-aware data is reviewed. Also, the main types of mechanisms used in these studies are identified. These mechanisms are related to monitoring, generalization, inference, feedback, energy management and privacy. Furthermore, a description of the mechanisms used in each study is presented.