Virtual Coaches, also known as e-coaches, are a disruptive technology in healthcare. Indeed, among other usages, they might provide cost-effective solutions for increasing human wellbeing in different domains, such as physical, nutritional, cognitive, social, and emotional. This paper presents a systematic review of virtual coaches specifically aimed at improving or maintaining older adults' health in the aforementioned domains. Such digital systems assume various forms, from classic apps, to more advanced conversational agents or robots. Fifty-six articles describing a virtual coach for older adults and aimed at improving their wellbeing were identified and further analyzed. In particular, we presented how previous studies defined their virtual coaches, which behavioral change models and techniques they adopted and the overall system architecture, in terms of monitoring solutions, processing methods and modalities for intervention delivery. Our results show that few thorough evaluations of e-coaching systems have been conducted, especially regarding multi-domain coaching approaches. Through our analysis, we identified the wellbeing domains that should be addressed in future studies as well as the most promising behavior change models and techniques and coaching interfaces. Previous work illustrates that older adults often appreciate conversational agents and robots. However, the lack of a multidomain intervention approach in the current literature motivates us to seek to define future solutions.
Eyes on the road, hands on the wheel" is a crucial principle to be taken into account designing interactions for current in-vehicle interfaces. Gesture interaction is a promising modality that can be implemented following this principle in order to reduce driver distraction and increase safety. We present the results of a user elicitation for gestures performed on the surface of the steering wheel. We asked to 40 participants to elicit 6 gestures, for a total of 240 gestures. Based on the results of this experience, we derived a taxonomy of gestures performed on the steering wheel. The analysis of the results offers useful suggestions for the design of in-vehicle gestural interfaces based on this approach.
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