Abstract
Facial expressions are a spontaneous way of perceiving emotions, which can provide information related to the cognitive state of a person. Facial expression recognition of the elderly is an important aid to better care them, according to their state of mind, although it can be a difficult task because their expressions might not be as easily perceived as those from younger persons. We proposed a model to classify the facial expressions of the elderly, presenting the differences between facial expression recognition in the elder and in other age group, as well as methods to surpass these difficulties. Viola Jones with Haar Features was used to extract the faces and Gabor Filter to extract the facial characteristics. These characteristics are classified using a Multiclass Support Vector Machine. We got an accuracy of 90.32%, 84.61% and 66.6%, when detecting the neutral state, happiness and sadness respectively in the elderly. In the other age group, we got an accuracy of 95.24%, 88.57%, and 80%, while detecting the neutral, happiness, and sadness states and concluded that aging influences negatively the facial expressions recognition tasks.

Abstract
The continuous use of the muscles in any kind of physical exercises results in muscular fatigue, which can be defined as the incapability of the muscle to perform with the same effectiveness over the course of time. The analysis of physical exercise intensity has great importance in various fields, including sports and physiotherapy. In this paper, the rate of blinking eyes and the change in shape of mouth throughout the physical exercise are analyzed using computer vision techniques, and compared with the perceived exertion. The experiments were done using the facial video of three athletes, grabbed during a stationary cycle of physical exercise, until maximal muscle activity was achieved. The perceived exertion was reported at the end of each minute. The blinking of the eyes and opening of the mouth were detected by counting the number of bright pixels in the region of interest of an eye and of the mouth. These regions were detected using the Viola and Jones algorithm. We have proved the existence of a correlation between the opening and closing of the mouth and the eye-blinking rates with the physical exercise intensity (i.e., the higher the exercise intensity, the higher the rate of eye-blinking and mouth opening and closing). We obtained 95% accuracy in blinking eye detection.

Abstract
Many cloud vision APIs are available on the internet to recognize emotion from facial images and video analysis. The capacity to recognize emotions under various poses is a fundamental requirement in the area of emotion recognition. In this paper, the performance of two famous emotion recognition APIs is evaluated under the facial images of various poses. The experiments were done with the public dataset containing 980 images of each type of five poses [full left, half-left, straight, half-right, and full-right] with the seven emotions (Anger, Afraid, Disgust, Happiness, Neutral, Sadness, Surprise). It has been discovered that overall recognition accuracy is best in Microsoft Azure for straight images, whereas the face detection capability is better in Google. The Microsoft did not detect almost any of the images with full left and full right profile, but Google detected almost all of them. The Microsoft API presents an average true positive value up to 60%, whereas Google presents the maximum true positive value 45.25%.

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
Online tools for dyslexic diagnosis and training are mostly: free-of-charge; children-oriented, consisting in a game-based interface proved a positive correlation between video games and dyslexia [1]; and, provide auto-evaluation questions that are automatically analyzed, given results regarding the need of seeking medical attention, since these tools are not a medical exam or diagnostic. Other platforms consist on exercises/tests for dyslexic people or with speech and language impairments, helping them in the training of the word pronunciation. Although, there is a lack of solutions that allow doctors to register the evolution of their patients. In this article, it is presented an accessibility and usability assessment of a Web platform that allows children to do exercises but also lets their doctors to keep track of their evolution through graphs and detailed statistics, allowing doctors to have information on a digital format, disproving the need for tests normally done on paper [2–4], and not having to manually register variables. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract
Average life expectancy of the humans has been increasing with the advancement of medicine, hence observing an aging of the population in general. Associated with aging, loss of cognitive ability and memory failure are often observed, which can have a great impact on the quality of life and autonomy of people who need to take medication on an hourly basis. In this work, we present the development of an application that helps to manage two key issues for the quality of life of the elderly: the time of medication and the time of medical consultations. The application is managed (information is added, altered or deleted) by a responsible, as a family member or health professional. After analyzing several solutions, it was verified that the biggest problem identified is the difficulty of interaction with the interface (sometimes it presents a lot of information and do not focus on functions of immediate necessity). In this context, we present a solution that focuses on two main objectives: first, to present a clear and simple list of medication and list of information of consultations; and second, to provide a simplified interface for the management of medication by a caregiver (child, nurse, and tutor). In the first development phase, we evaluated the usability of this interface, with ten health care professionals, who evidenced the potentiality of the solution presented here.