Abstract
Portugal, as part of the European Union, has general legislation regarding accessibility and inclusion for general purposes, particularly for education. There are several international and national initiatives, including some projects. However, disabled and non-disabled people still do not share equal opportunities. In this project a proposal for a remote class system is presented, which includes sign language interpretation, targeted at those students who cannot be physically present in the classroom and/or need sign language interpretation. The system is based on audio and video communication between the classroom, the student and an interpreter, so that the student can access and understand the content of the class in real-time, as well as be able to interact with the professor and classmates. A prototype is being developed in conjunction with the Portugal Telecom Foundation, which should be a step forward to a new full-featured service targeted at educational institutions and disabled students. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract
Aging is a natural process inherent in being human. During the aging process a person's physical and mental condition will degrade, imposing limitations on their life, which can have a great impact on their well-being. Although they are common to all humans, the consequences of aging can be aggravated by the decline in social relations and contact with family and friends. It is therefore of the utmost importance to maintain these relationships throughout life. In this sense, we intend to develop a system to support these people, allowing them to overcome their limitations, promoting and reinforcing the bonds between the user and the elements of his family and group of friends, using the technology. In this article we discuss the prototyping of a support system for the elderly to combat the lack of interaction between these individuals and their social group. With the use of prototyping it s intended a previous validation of the concept and functionalities of this system. The user is placed within the development process and, in this way, it is possible to evaluate the Human-Machine Interaction component and to detect possible problems so that they can be solved in a timely manner. This is an iterative process in which the system is constantly evaluated and readjusted until it is validated.

Abstract
The general increase in life expectancy and the consequent ageing of the general population impose major challenges to modern societies. Most elderly people experience the typical problems related to old age, such as chronic health problems, as well as sensory and cognitive impairments. In addition, in today’s modern societies, where families have less and less time to look after their older relatives, the isolation of the elderly is a real concern and a highly recurrent problem, which is enhanced when they live alone. To solve, or at least minimize, these problems, a smart home monitoring system was developed, as presented and described in this paper. This solution is implemented based on a sensory network which detects anomalous behaviors, immediately triggering a warning to the caregiver or family. A strong concern when developing a project of this kind is the physical security of the elderly. Houses tend to have hazardous objects and characteristics that may inflict serious injuries to their occupants or, in extrema, even death. As time goes by, the elderly start losing muscle mass and osteoporosis may appear, as well as vision and hearing impairments, which increase the likelihood of falling. Several other serious accidents may also occur, such as gas leaks, floods and fire outbreaks. Therefore, this population would strongly benefit from a solution which helps predict and even prevent accidents before they happen. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract
In this review the objective is to search for technologies that supervise the exercise or physical activity of people suffering from Peripheral Arterial Disease (PAD) at home or in the community. Patients with PAD have walking limitations and their quality of life progressively deteriorates. The regular practice of exercise can help mitigate these effects and even improve their health status. The methodology used was to search for scientific articles published since 2008, with the final result of 18 articles. The results show the most frequent technologies used are based on the accelerometer device, with the tests being performed on a treadmill at a hospital. The hospital tests are expensive, so a useful and viable alternative is the usage of mobile devices to help the health professionals record the exercise performed by their patients suffering with PAD. © Springer International Publishing AG, part of Springer Nature 2018.

Abstract
This paper presents an overview of the donation based crowdfunding state of the art, establishing a classification scheme to analyze the major platforms, and discussing current research trends and future challenges of crowdfunding as a social inclusion instrument. In many social exclusion situations crowdfunding is the last stronghold to ensure the access to basic commodities, essential to the daily life and well-being of individuals. Despite the commercial success of many crowdfunding platforms, this study shows future research opportunities in the crowdfunding as an inclusion mechanism that can trigger a broader adoption for social causes. The high social impact of the research contributions in this domain can also contribute to make it a hot topic in the upcoming years.

Abstract
Facial expression analysis has a wide area of applications including health, psychology, sports etc. In this study, we explored different methods of automatic classification of exercise intensities using facial image processing of a subject performing exercise on a cycloergometer during an incremental standardized protocol. The method can be implemented in real time using facial video analysis. The experiments were done with images extracted from a 12 min HD video collected in laboratorial normalized settings (TechSport from the University of Trás-os-Montes e Alto Douro) with a static camera (90° angle with face and camera). The time slot for video to extract images for a particular class of exercise intensity is correspondence to the incremental heart rate. The facial expression recognition has been performed mainly in two steps: facial landmark detection and classification using the facial landmarks. Luxand application was used to detect 70 landmarks were detect using the adaptation of code available in Luxand application and we applied machine learning classification algorithms including discriminant analysis, KNN and SVM to classify the exercise intensities from the facial images. KNN algorithms presents up to 100% accuracy in classification into 2 and 3 classes. The distances between a lowermost landmark of the faces, which is indicated in landmark number 11 in the Luxand application, and the 26 landmarks around mouth were calculated and considered as features vector to train and test the classifier. Separate experiments were done for classification into two, three, and four classes and the accuracy of each algorithm was analyzed. From the overall results, classification into two and three classes was easy and resulted in very good classification performance whereas the classification with four classes had poor classification performance in each algorithm. Preliminary results suggest that distinguishing more levels of exertion, might require additional feature variables. © 2018 IEEE.