Christiana Tsiourti

Widespread acceptance and use of personalized mobile devices facilitates the provision of the ubiquitous mobile communications and computing applications that enable the human Quality of Life (QoL) improvement. However, there are multiple human factors influencing these applications, stemming from their users' needs, expectations, and ways of maximizing their experience and the impact on their QoL. For a successful adoption of these applications, our mobile technologies lab, mQoL, employs an iterative, user-centric, Living Lab approach for the applications' design and evaluation. This paper introduces the concept of mobile technologies for QoL specifically aiming to first understand the individual's QoL from information available in mobile devices, i.e., assess physical, psychological, social or environmental aspects of a daily life of an individual, and, based on this understanding, provide services to improve this individual's QoL. This paper also explains the methodological aspects of our research, including transdisciplinarity aspects, and delineates the research challenges for a Living Lab approach at large.

Use of public transportation is on a rise, enabling greener cities and improvement of the quality of life of the city residents. The challenge for the public transportation system is that its demands are non linear and the passengers' experience depends on many human factors. UnCrowdTPG is a mobile service and a research platform that has been developed for understanding the mobility patterns of the users of public transportation services in Geneva (TPG), as well as their experience with respect to the crowds perceived aboard the vehicles. UnCrowdTPG models algorithmically this experience using crowdsourcing techniques and it provides to the individual estimations of the future expected experiences aboard, thus enabling them to better plan their journeys with respect to the crowds. In this paper we position the UnCrowdTPG service as a research platform. Additionally we discuss the research questions in areas like local governance and public healthcare supported by the data analysed collectively from all UnCrowdTPG users. We also discuss the challenges for implementing the truly smart transportation system in a small-sized European city like Geneva.

Advances in miniaturized computing, storage and communication resources for personal wearable electronics devices, as well as the availability of diverse sensors for state assessment enable the development of a wide variety of wearable body area network (BAN) systems for psychophysiological measurements. These systems pave the way for acquisition of quality data relevant for research studies, amongst others, on the autonomic nervous system (ANS) activation in emotion. We present a high-level overview of BAN and its features, and we review 173 publications that report research studies on emotion activation and particularly 15 BAN systems employed in these studies. We discuss each BAN in terms of its capacity for ambulatory, i.e., out of the laboratory, assessment of the ANS activation in emotion. Finally, we highlight the design challenges to be addressed to make BAN systems effective for a wide range of applications to support users wellbeing and overall Quality of Life improvement. This paper provides knowledge to those interested in (ambulatory) assessment of the ANS activation on the set of systems currently used in research, and it aims to highlight opportunities for scientists and practitioners in, amongst others, the affective computing domain, enabling them to reflect upon their BAN requirements and study designs.