During the last decade, the living lab and co-creation concepts have started being blended with the Responsible Research and Innovation approach, aiming to evaluate potential societal anticipations toward fostering an inclusive RRI behavior. Teaching co-creation concept and living lab methodologies to university students has started been considered as valuable for future researchers along with the demand of companies and public sectors which turn toward user-center techniques for inspiration to develop innovative and services. To this end, the scientific publications presenting work on teaching co-creation and living lab methodologies are not so many while there are no published research studies on experiential learning activities for teaching co-creation and living lab approaches to university students. This study presents a course based on living labs and co-creation methodologies through experiential learning activities, consisted of four different lectures and an open event. The study involves stakeholders from the academia, the citizens, and the public sector. The results show that lectures with the participation of end-users were the most enjoyable. Furthermore, students thought that they learned the most when they first met the end-users. This lecture was perceived as a successful way to gain methodical knowledge for user-centered design and software development.

As a result of several years of European funding, progressive introduction of assistive technologies in our society has provided many researchers and companies with opportunities to develop new information and communication technologies aimed at overcoming the digital divide of those at a greater risk of being left behind, as can be the case with healthy older people and those developing cognitive decline and dementia. Moreover, in recent years, when considering how information and communication technologies have been integrated into older people’s lives, and how technology has influenced these individuals, doubts remain regarding whether technologies really fulfil older users’ needs and wishes and whether technologies developed specifically for older users necessarily protect and consider main ethical values. In this article, we address the relevance of privacy, vulnerability and preservation of autonomy as key factors when involving older individuals as target users for information and communication technology research and development. We provide explanatory examples on ethical issues involved in the particular case of developing different types of information and communication technology for older people (from robotics to serious games), what previously performed research tells us about older adults’ preferences and wishes for information and communication technology and what steps should be taken into consideration in the near future.

To date, the use of synthetic data generation techniques in the health and wellbeing domain has been mainly limited to research activities. Although several open source and commercial packages have been released, they have been oriented to generating synthetic data as a standalone data preparation process and not integrated into a broader analysis or experiment testing workflow. In this context, the VITALISE project is working to harmonize Living Lab research and data capture protocols and to provide controlled processing access to captured data to industrial and scientific communities. In this paper, we present the initial design and implementation of our synthetic data generation approach in the context of VITALISE Living Lab controlled data processing workflow, together with identified challenges and future developments. By uploading data captured from Living Labs, generating synthetic data from them, developing analysis locally with synthetic data, and then executing them remotely with real data, the utility of the proposed workflow has been validated. Results have shown that the presented workflow helps accelerate research on artificial intelligence, ensuring compliance with data protection laws. The presented approach has demonstrated how the adoption of state-of-the-art synthetic data generation techniques can be applied for real-world applications.

It has been shown that exergames have multiple benefits for physical, mental and cognitive health. Only recently, however, researchers have started considering them as health monitoring tools, through collection and analysis of game metrics data. In light of this and initiatives like the Quantified Self, there is an emerging need to open the data produced by health games and their associated metrics in order for them to be evaluated by the research community in an attempt to quantify their potential health, cognitive and physiological benefits. We have developed an ontology that describes exergames using the Web Ontology Language (OWL); it is available at http://purl.org/net/exergame/ns #. After an investigation of key components of exergames, relevant ontologies were incorporated, while necessary classes and properties were defined to model these components. A JavaScript framework was also developed in order to apply the ontology to online exergames. Finally, a SPARQL Endpoint is provided to enable open data access to potential clients through the web. Exergame components include details for players, game sessions, as well as, data produced during these game-playing sessions. The description of the game includes elements such as goals, game controllers and presentation hardware used; what is more, concepts from already existing ontologies are reused/repurposed. Game sessions include information related to the player, the date and venue where the game was played, as well as, the results/scores that were produced/achieved. These games are subsequently played by 14 users in multiple game sessions and the results derived from these sessions are published in a triplestore as open data. We model concepts related to exergames by providing a standardized structure for reference and comparison. This is the first work that publishes data from actual exergame sessions on the web, facilitating the integration and analysis of the data, while allowing open data access through the web in an effort to enable the concept of Open Trials for Active and Healthy Ageing.

Conventional clinical cognitive assessment has its limitations, as evidenced by the environmental shortcomings of various neuropsychological tests conducted away from an older person’s everyday environment. Recent research activities have focused on transferring screening tests to computerized forms, as well as on developing short screening tests for screening large populations for cognitive impairment. The purpose of this study was to present an exergaming platform, which was widely trialed (116 participants) to collect in-game metrics (built-in game performance measures). The potential correlation between in-game metrics and cognition was investigated in-depth by scrutinizing different in-game metrics. The predictive value of high-resolution monitoring games was assessed by correlating it with classical neuropsychological tests; the area under the curve (AUC) in the receiver operating characteristic (ROC) analysis was calculated to determine the sensitivity and specificity of the method for detecting mild cognitive impairment (MCI). Classification accuracy was calculated to be 73.53% when distinguishing between MCI and normal subjects, and 70.69% when subjects with mild dementia were also involved. The results revealed evidence that careful design of serious games, with respect to in-game metrics, could potentially contribute to the early and unobtrusive detection of cognitive decline.