Recent studies in social robotics show that it can provide economic efficiency and growth in domains such as retail, entertainment, and active and assisted living (AAL). Recent work also highlights that users have the expectation of affordable social robotics platforms, providing focused and specific assistance in a robust manner. In this paper, we present the AMIRO social robotics framework, designed in a modular and robust way for assistive care scenarios. The framework includes robotic services for navigation, person detection and recognition, multi-lingual natural language interaction and dialogue management, as well as activity recognition and general behavior composition. We present AMIRO platform independent implementation based on a Robot Operating System (ROS). We focus on quantitative evaluations of each functionality module, providing discussions on their performance in different settings and the possible improvements. We showcase the deployment of the AMIRO framework on a popular social robotics platform—the Pepper robot—and present the experience of developing a complex user interaction scenario, employing all available functionality modules within AMIRO.

With the continuous ageing of the population, the demand for different healthcare services is increasing at a fast pace. At the same time, the number of caregivers is limited and the cost of well-being is increasing. Therefore, there is a recognized need for technologies that assist elderly people in their daily activities and ensure their safety along with their social integration while maintaining a higher degree of independence. One important aspect in the development of such technologies is their easy acceptance by elderly users. Traditional human-machine interfaces have always represented a barrier for the acceptance of new devices by non-technical people in general and by elderly or people with special needs in particular. In this paper, we propose a multimodal interface designed to match the requirements of Ambient Assisted Living (AAL) systems and to fulfill the needs of elderly people who are the main users of this interface. The interface is multilingual, it supports two languages (English and Romanian) and it can process both speech and gesture commands. The interface is developed using HTML5, JavaScript, CSS3 and integrates Google Speech Service along with other services. It is able to adapt itself to any screen size and to work flawlessly across different platforms. The interface was developed and tested within the "Artificial intelligent ecosystem for self-management and sustainable quality of life in AAL" (CAMI) project. Both the interface and the results of laboratory tests are presented in this paper.

The increase in life expectancy and the slumping birth rates across the world result in lengthening the average age of the society. Therefore, we are in need of techniques that will assist the elderly in their daily life, while preventing their social isolation. The recent developments in Ambient Intelligence and Information and Communication Technologies have facilitated a technological revolution in the field of Ambient Assisted Living. At present, there are many technologies on the market that support the independent life of older adults, requiring less assistance from family and caregivers, yet most of them offer isolated services, such as health monitoring, reminders etc, moreover none of current solutions incorporates the integration of various functionalities and user preferences or are formally analyzed for their functionality and quality-of-service attributes, a much needed endeavor in order to ensure safe mitigations of potential critical scenarios. In this paper, we propose a novel architectural solution that integrates necessary functions of an AAL system seamlessly, based on user preferences. To enable the first level of the architecture's analysis, we model our system in Architecture Analysis and Design Language, and carry out its simulation for analyzing the end-to-end data-flow latency, resource budgets and system safety.

Adaptive user interfaces can be more effective in increasing accessibility of the interaction between people and systems, especially for elderly or people with different impairments such as cognitive impairments in people with dementia. There are two possible types of adaptation for interfaces: navigation and content-based adaptation. Both types of adaptation must be made based on the context (devices that are used) and on the user profile. This paper presents a method for interface adaptation using user classification. Users are classified based on their interactions with the interface.

With the help of telemedicine, patients can be treated by remote specialists through teleconference. In addition to the communication between health professionals and their patients, telemedicine should coordinate and manage the day-to-day operations and it must have a well-defined service request and incident management process. A support process that includes service request and incident management helps telemedicine to prevent problems, to identify rapidly the causes of problems when they occur and to help in remediating the issues. To allow faster support and help from the system to the patients in an automated and user-friendly approach, the service request and incident management process should integrate a chatbot.

Physical activity represents a key element for elderly people to maintain a healthy life. This paper presents a game for supporting and stimulating elderly people in performing physical activity. The game is composed of different type of exercises that are selected based on the user's profile and health status. The results are presented to the user in multiple ways that are correlated with his/her emotional state and preferences in order to increase the satisfaction of each user experience.