Abstract

Abstract
The collection of health and fitness longitudinal data can be used to model disease progression and shape new algorithms to diagnose and predict health hazards. Continuously tracking vital signs, in particular heart rate and skin temperature, can be very informative by using models and algorithms to predict and notify the user about when he might be falling ill. With the current wearable devices and the proper algorithms, the individual can be permanently monitored, which might be much more interesting than a one-off reading comparison with the population average, made by a doctor. It would be possible to intervene earlier and to prevent somebody from becoming seriously ill. From a broader perspective, the knowledge about a user’s health can be considered as an element of that user’s context and be used by context aware applications to provide higher value to the user. After the trivialization of the data acquisition sensors, wearable devices, and raw data, the next logical step is the development of contained software components that can infer and produce knowledge from the raw data. These components and the knowledge they produce can be used by all sorts of applications in order to further customize their usage by a specific user. Customization and context awareness, in regard to health, is a wide field for research and there are a multitude of proposals for models and algorithms. In this review work we searched for software components (frameworks, software libraries, etc.), freely available and that can be used as building blocks for other computer systems by software developers. Copyright

Abstract

Abstract
To receive a degree from a Higher Education Institution (HEI), the students must successfully undergo the necessary exams, which, most times, require the physical presence of the student in a room where he/she will solve and answer the exams' questions using the traditional pen and paper. This is a well-known and reliable method to evaluate the students, in which the physically presence is a reliable way to diminish the possibilities of fraud. Currently, the modern Learning Management Systems (LMS) are able to provide the necessary features to execute the evaluations activities online, on the software platform. These systems and features can be used in a blended model, in which the students are required to be physically present, in a similar form to a traditional on site exam, and the exam is executed using a LMS. The exam room is equipped with Personal Computers (PC), which are configured with the necessary means to access the LMS and assure that a higher risk of fraud is not introduced by the usage of the PCs and the LMS as support for the exams. We designated this model, as the b-eval model. The adoption of this model requires some changes in the professors' practices, as well as the introduction of more technological means to support the increase in PCs and LMS usage. The professors must design their evaluation process in order to incorporate the features and restrains posed by the PCs and the LMS. In some scenarios, this adoption is advantageous for the professor and for the students, considering that a properly designed exam can easily be executed by the students and instantaneously evaluated and graded. Otherwise, the traditional process takes much longer, as the professor must collect the paper exams, which he will later evaluate and grade. The process can take several days or even weeks. In this position paper we discuss the introduction of the b-eval model, as well as an assessment methodology for its adoption.

Abstract
For oncological patients, the introduction of palliative care in the early stages of the disease’s progression can have great benefits. The Portuguese government recently introduced a program to provide home palliative care support by creating specialized mobile teams, able to track, visit and address the patients’ problems. These teams must be available for the patient, when necessary and if necessary. The teams must also have updated knowledge about the daily evolution of the patients’ health. The Douro Sul Healthcare Centers, together with the University of Trás-os-Montes e Alto Douro, developed and implemented an ICT system to track the status of each and every one of the patients. The system has several components, including: a mobile app for the patients or their caregivers to report daily how the patient’s symptoms have evolved over the last 24 h; a web app for the teams to browser their patients’ status. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract
In the later stages of the aging process, an elderly person might need the help of a family member or a caregiver. Technology can be used to help to take care of elderly persons. Autonomous systems, using special interfaces, can collect information from elderly people, which might be useful to predict and recognize health related problems or physical security problems in real time. The emerging technology of image processing, in particular, the emotion recognition, can be a good option to use in elderly care support systems. In this article, we implemented a Microsoft Azure – Emotion SDK to recognize emotion of elderly that able to detect faces and recognize emotions in real time and to be used for elderly care support. The analysis is done with an online video stream, which analyzes facial expression, so that in case of a critical emotion, e.g., if an elderly is very sad or crying, it will inform a caregiver or related entity. From the experiment, we concluded that emotion recognition is a reliable technology to be implemented in real time elderly care. © Springer International Publishing AG, part of Springer Nature 2018.