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Family elderly caregiving is one of the preferred approaches for sustaining aging in place. While elderly people usually advocate for such an aging paradigm, supporting it represents an important challenge for family members, particularly in terms of coordination, resource allocation, and articulation of caregiving tasks. This paper presents Hermes, a digital assistant designed to help family caregiving stakeholders deal with the underlying challenges of such a process. Although the system is still at the prototype stage, its usability and perceived usefulness were evaluated with a sample of the target population. The obtained results are highly promising, showing that this challenge can effectively be addressed using technology, as well as generating a potential positive impact on informal family caregivers and older adults.

This chapter builds upon the need to adopt a more comprehensive approach when designing computer-supported technology to mediate social interaction between older adults and other generations of family members. Recognizing the complexity and heterogeneity of this communication scenario, the chapter shows the need to consider the culture as a key factor for reusing HCI design knowledge when conceiving new technology to mediate intergenerational social interactions. Considering a cultural perspective, this chapter discusses similarities and differences in the intergenerational social interaction process in Latin American and Western countries. On the one hand, the identified similitudes help reuse existing design knowledge. On the other hand, the identified differences inform the design of new solutions to mediate intergenerational communication. Understanding the underlying socio-cultural traits of the social inter-action scenario allows us to determine how to reuse the knowledge gained during the previous two decades of HCI research with older adults, and thus design better interaction mechanisms for the next generation of systems for this application domain.

The proliferation of social media tools for facilitating interpersonal communication has inadvertently modified the ways in which intergenerational exchanges are supported. However, such technology has generally not acknowledged the complexity of designing social interaction mechanisms involving older adults, where the provided technology services and the actual needs of elderly people are not necessarily aligned. As a way to bridge this gap, we developed SocialConnector, a computer-supported domestic system that facilitates and mediates social interaction among older adults and other family members using their preferred interaction paradigms and communication media. This paper reports on the results of an empirical in-the-wild study evaluating the mediation effect of the proposed system with a sample of nine families over nine weeks. The study results show that older adults using SocialConnector were more engaged in interacting within their close social networks, whereas social awareness notification messages did encourage user participation between family members and their older adults. By addressing the lessons learned in this study, social computing designers and practitioners would be in a better position to identify plausible solutions that would improve user experience and the effectiveness of computer-supported mediation strategies in intergenerational communication settings.

Advances in medical science allow people to live longer and more independently than some decades ago. However, this does not directly help older adults improve their mental wellbeing. Several studies show that elderly people usually suffer from some level of social isolation that negatively impacts on their physical and mental conditions. As a way to address such a problem, this paper presents Visitrack, a pervasive and unobtrusive service conceived to monitor the social activity of older adults living at home. Based on sensing data retrieved and processed by the system, it can take several actions. For instance, informing family members and friends about long periods with no social activity at the older adult’s home. The proposed service has been evaluated through a controlled experimental study, obtaining highly accurate results.

The irruption of computer-based technology in social interaction has negatively affected the way in which elderly people interact with their family members, because they are, in some cases, reluctant to adopt new digital media. Given that literature suggests that seniors spend a significant part of their day watching television, we argue that Smart TV applications can be an effective way to provide them access to ambient assisted living services. This paper reports the design and use of a Smart TV-based application that promotes social interaction between older adults and their family members through social media. The system runs on a LED screen, extended with smart functionalities provided by Google Chromecast. The social interaction features provided by the system include exchanging email messages and sharing photos that are automatically retrieved from the accounts of family members in social media feeds. The system was evaluated with a group of expert users as well as with a sample of end-users. Older adults participating in the study praised the new possibilities offered by the prototype application as a way to better engage with family-generated content, thus facilitating their social integration.

The promise of pervasive computing applications is to surround people with affordable, transparent and unobtrusive technology. However, several barriers including usability concerns, a lack of perceived usefulness, and low technology self-efficacy may jeopardize the successful adoption of ambient assisted living AAL systems, particularly by the elderly. Following the development of the SocialConnector system, which mediates and coordinates the communication effort of family members with their elders, this paper describes the iterative design process conducted to help improve the acceptance of the system by end-users. This process considered the implicit and explicit concerns and expectations of the intended target users, and it involved three improvement cycles along an action research approach. Through this process, we obtained a set of lessons learned that aim to describe how to unobtrusively introduce sensing and monitoring technology at the home of the elderly. Keeping simple yet meaningful interaction metaphors helps increase the learnability and perceived usefulness of AAL technology by the elderly.If older adults perceive the value of having such kinds of tools installed in their homes, then they are prone to assume them as part of their lives. Likewise, situational and activity awareness mechanisms, such as visual notification badges and audio-enhanced user interfaces, can be used to persuade the elderly to approach the system and eventually use it. Finally, the design of AAL solutions also requires active consideration of the needs and attitudes of other family members, particularly those who assume an active role in the caring process of their elders.

Background: The rise of mobile Web-based technologies has diversified the mechanisms used by people to socialize, which results in issues in family communication. Among these concerns, the reluctance of older adults to use digital media may cause them social isolation, leading to negative effects in their physical and mental health.

Awareness has been identified as a key element that affects the quality of collaboration. Several studies indicate that awareness mechanisms to support collaborative learning activities should include factors and stimuli from the students’ context and social interactions. This contributes to enhance the collaboration process and the learning experience of the students. This paper proposes a behaviour awareness mechanism to support collaborative learning in undergraduate learning scenarios. This mechanism has been designed to provide personal and social awareness to students about both, their own and their peers learning behaviour. Moreover, this mechanism encourages reflection and promotes social interactions among students in order to improve the effectiveness of collaborative learning. The article also describes and evaluates a prototype of the proposed mechanism and its implementation in a collaborative mobile learning application, using a case study. The preliminary results show that this proposal helps promote collaborative learning in undergraduate learning contexts.

Current assistive technologies can improve the quality of life of people who have been diagnosed with different forms of Social Communications Disorders (SCD). In this paper we describe the way in which we have approached an assistive system for improving SCD, based on human-avatar interaction. Since the final development is in progress, this paper contributes with a general taxonomy that classifies the different kinds of interaction between humans and avatars, including the relationship among them and their communication skills. These skills are typically training to treat SCD.

The automatic recognition of human emotions is used to support several computing paradigms, like affective, positive and pervasive computing. Histograms of oriented gradients HOG have been successfully used with such a purpose, by processing facial images. However, the results of using HOG vary depending on the position of the facial components in the image used as input. This paper presents an extension to the HOG method, which was named Landmark-based Histograms of Oriented Gradients LaHOG, that not only calculates HOG blocks in the whole face, but also in specific positions around selected facial landmarks. In this sense, the new method is more robust than its predecessor. In order to evaluate the capabilities and limitations of this proposal, we used it to recognize emotions in face images from the FACES database. In such a process we used two classification strategies: support vector machines and logistic regression. The results show that the extended method significantly surpasses the performance of HOG in the tested database.

It is well-known that physical activities contribute to keep the people healthy. However, the modern life style impacts negatively on the amount of physical activity that we do during the day. Many times the people do not perform enough exercise because they are not aware of the amount of physical activity that they have done. In order to make the persons aware of this aspect of his life, this article presents a mobile application that monitors the amount of exercise they do every day and it informs properly to the user. The system, named AMOPA, allows caregivers or doctors monitoring particular patients, to access this information remotely in order to support the person being monitored. The system was evaluated using laboratory tests, and the results indicate a good performance and accuracy in the detection of the people physical activities. Moreover, the monitored process has a low impact on the energy consumption of the devices used to capture and process the information.

A noise-robust algorithm for segmentation of breath events during continuous speech is presented. The built-in microphone of a smartphone is used to capture the speech signal (voiced and breath frames) under conditions of a relatively noisy background. A template matching approach, using mel-cepstrograms, is adopted for constructing several similarity measurements to distinguish between breath and non-breath frames. Breath events will be used for lung function regression.

Typically mobile and ubiquitous software applications provide services to mobile workers to help them increase their performance, effectiveness and eventually the satisfaction while doing their jobs. These services are directly related to the characterization of the activities to be supported. Based on such a characterization the designers of these solutions can envision the services that should be provided by the new system. Few guidelines are available to characterize mobile activities from an IT support point of view, therefore the designers have to guess the services to be embedded in these solutions. This paper provides a first step to address such a problem, identifying the context variables that characterize the mobile activities. Moreover, an ontology of activity characteristics and some design guidelines are provided to determine which supporting services can be used to address activities according to their characteristics. This proposal was conceived based on the empirical observation of the work performed by the medical personnel at an emergency room of a public hospital. Further analysis is required to generalize this proposal, in order to address mobile work in other scenarios.

Several social computing participation strategies, such as crowdsensing and crowdsourcing, use mobile ad hoc or opportunistic networks to support the users activities. The unreliability and dynamism of these communication links make routing protocols a key component to achieve efficient and reliable data communication in physical environments. Often these routing capabilities come at expenses of flooding the network with a huge amount of topology control information (TCI), which can overload the communication links and dramatically increase the energy consumption of the participating devices. In previous works the authors have shown that predicting the network topology in these work scenarios helps reduce the number of control packets delivered through the network. This saves energy and increases the available bandwidth. This paper presents a study that extends the authors’ previous works, by identifying the impact of predicting the TCI generated by routing protocols in these networks. The prediction process is done following a history-based approach that uses information of the nodes past behavior. The paper also determines the predictability limits of this strategy, assuming that a TCI message can be correctly predicted if it appeared at least once in the past. The results show that the upper-bound limit of the history-based prediction approach is high, and that realistic prediction mechanisms can achieve significant ratios of accuracy. Mobile collaborative applications and routing protocols using mobile ad hoc or opportunistic networks can take advantage of this prediction approach to reduce network traffic, and consequently, the energy consumption of their devices.

Depression is a mental illness that is difficult to diagnose and treat. This mental disorder affects many older adults due several reasons, for instance because of their physical limitations and the natural reduction of their social circle. This article presents a system for monitoring the mood of the elderly through voice processing. The system is particularly focused on detecting sadness, which allows caregivers of family members to react on-time in supporting the person in need. The sadness recognition is done by classifying emotions in groups, according to the Circumflex Model of Affect. After evaluating the system using several emotion databases, the obtained results indicate that this solution is able to recognize 94% of the cases in men and 79% in women. This solution can be embedded in ubiquitous systems that monitor the mood of people in several scenarios.

The rise of Internet and ubiquitous technologies have spread and diversified the social media used by people to interact among them. Unfortunately most older adults are not able to use these solutions. This situation isolates them and negatively affects their physical and mental health. Aiming to improve mood in older adults, and helping them overcome the negative effects of social isolation, we have developed a computer-based intermediary system, that we called Social Connector. This system is capable of boosting the social interaction between an elder and his/her close relatives; e.g. adult children and grandchildren. The system can also be used as a sensor of elders' social interactions and mood. The preliminary evaluation results indicate that the system is well accepted by older adults, and it can be used to boost social interactions with their relatives.

Embedding context-aware self-adaptation mechanisms in pervasive systems is key to improve their acceptance by the users. These mechanisms involve a precise definition of the software structures that enable adding, removing or replacing components of the system to perform the adaptations. Typically the definition of these mechanisms is a complex and time consuming task. This paper presents a model-driven engineering approach to generate these context-aware self-adaptation mechanisms. The use of models transformations to define these mechanisms helps to reduce the complexity and effort required to define them. In order to illustrate the usefulness of the proposed approach, this paper reports its application to the development of a context-aware notification service.

Active aging aims at promoting physical activity, socialization and participation in society as a mechanism to improve physical and mental health. We explore the use of a mobile, context-aware application to help elders transform their grocery shopping experience into an activity that promotes active aging. We describe the design and formative evaluation of WaSSAA, a mobile application to persuade elders to exercise and socialize while sharing grocery prices and promoting "smart" grocery shopping. WaSSAA uses location information to promote social encounters and to ask shoppers to gather price information for fellow users, and the accelerometer to estimate physical activity and reward its user. Results of a formative evaluation of the usefulness of WaSSAA with 16 elders shows that older adults are aware and sensitive to grocery prices and find the application useful to guide them when comparing prices during grocery shopping. They also perceive grocery shopping as a social activity and welcome WaSSAA's services to encourage in-person encounters.