Abstract
Stress is a highly complex, subjective and multidimensional phenomenon. Nonetheless, it is also one of our strongest driving forces, pushing us forward and preparing our body and mind to tackle the daily challenges, independently of their nature. The duality of the effects of stress, that can have positive or negative effects, calls for approaches that can take the best out of this biological mechanism, providing means for people to cope effectively with stress. In this paper we propose an approach, based on mouse dynamics, to assess the level of stress of students during online exams. Results show that mouse dynamics change in a consistent manner as stress settles in, allowing for its estimation from the analysis of the mouse usage. This approach will allow to understand how each individual student is affected by stress, providing additional valuable information for educational institutions to efficiently adapt and improve their teaching processes.

Abstract
In this busy society of ours people push their limits to work better and more in order to remain competitive with their peers. Nonetheless, working longer hours does not necessarily improves productivity nor performance. In order to prevent the negative consequences of this increasing trend, the evolution of performance throughout the day of work should be more closely monitored. This could avoid undesirable states or even breakdowns, which have social and economical implications. In this work we measure user performance through their interaction with the computer. We monitor its evolution during a day of work and how different types of music may increase or decrease its natural daily degradation. We conclude that the relationship between types of music and its effects is not universal and depends, among other things, on the musical profile of the individual. A prototype for a distributed music recommendation service is presented that suggests musics at an individual and group level, based on user musical profiles and objectives.

Abstract
Nowadays, our lifestyle can lead to a scatter of focus, especially when we attend to several tasks in parallel or have to filter the important information from all the remaining one. In the context of a computer this usually means interacting with several applications simultaneously. Over the day, this significant demand on our brain results in the emergence of fatigue, making an individual more prone to distractions. Good management of the working time and effort invested in each task, as well as the effect of breaks at work, can result in better performance and better mental health, delaying the effects of fatigue. This paper presents a non-intrusive and non-invasive method for measuring distraction and fatigue in an individual and in a group of people. The main aim is to allow team managers to better understand the state of their collaborators, thus preparing them to take better decisions concerning their management.

Abstract
Mental fatigue is a concern for a range of reasons, including its negative impact on productivity and quality of life in general. The maximal working capacity and performance of an individual, whether physical or mental, generally also decreases as the day progresses. The loss of these capabilities is associated with the emergence of fatigue, which is particularly visible in long and demanding tasks or repetitive jobs. However, good management of working time and of the effort invested in each task, as well as the effect of breaks at work can result in better performance and better mental health, delaying the effects of fatigue. In this paper a model and prototype are proposed to detect and monitor fatigue, based on behavioral biometrics (Keystroke Dynamics and Mouse Dynamics). Using this approach, the aim is to develop leisure and work context-aware environments that may improve quality of life and individual performance, as well as productivity in organizations. © Springer International Publishing Switzerland 2016.

Abstract
In recent years, mobile devices and applications have known a growth that is unprecedented in any other technological field, reaching virtually all aspects of our lives including sports, leisure, social relationships or health. This paper describes the development of an environment to assess auditory emotional recognition based on a mobile application. The primary aim of this work is to provide a valuable instrument that can be used both in research and clinical settings, responding to the strong need of validated measures of emotional processing in Portugal. The secondary aim is to study behavioral features, acquired unobtrusively from the interaction of the participant with the device, in search for a relationship with medical conditions, cognitive impairments, auditory emotional recognition or sociodemographic indicators. This will establish the foundation for the prediction of such aspects based on the analysis of people's interaction with technological devices, providing new potentially interesting diagnostic tools.

Abstract
In our daily life, we often have a sense of being exhausted due to mental or physical work, together with a feeling of performance degradation in the accomplishment of simple tasks. This is in part due to the fact that the working capacity and the performance of an individual, either physical or mental, generally decrease as the day progresses, although factors like motivation also play a significant role. These negative effects are especially significant when carrying out long or demanding tasks, as often happens in an educational context. In order to avoid these effects, initiatives to promote a good management of the time and effort invested in each task are mandatory. Such initiatives, when effective, can have a wide range of positive effects, including on the performance, productivity, attention and even mental health. Seeking to find a viable and realistic approach to address this problem, this paper presents a non-invasive and non-intrusive way to measure mental workload, one of the aspects that affects mental fatigue the most. Specifically, we target scenarios of e-learning, in which the professor may not be present to assess the student's state. The aim is to create a tool that enables an actual management of fatigue in such environments and thus allows for the implementation of more efficient learning processes, adapted to the abilities and state of each student.