Mid-air haptic feedback constitutes a new means of system feedback in which tactile sensations are created without contact with an actuator. Though earlier research has already focused on its abilities to enhance our experiences, e.g. by increasing a sense of immersion during art exhibitions, an elaborate study investigating people's abilities to identify different mid-air haptic shapes has not yet been conducted. In this paper, we describe a user study involving 50 participants, with ages between 19 -77 years old, who completed a mid-air haptic learning experiment involving eight different mid-air haptic shapes. Preliminary results showed no learning effect throughout the task. Age was found to be strongly related to a decline in performance, and interestingly, significant differences in accuracy rates were found for different types of mid-air haptic shapes.

Interfaces that allow users to interact with a computing system by using free-hand mid-air gestures are becoming increasingly prevalent. A typical shortcoming of such gesture-based interfaces, however, is their lack of a haptic component. One technology with the potential to address this issue, is ultrasound mid-air haptic feedback. At the moment, haptic sensations are typically designed by system engineers and experts. In the case of gestural interfaces, researchers started involving non-expert users to define suitable gestures for specific interactions. To our knowledge, no studies have involved-from a similar participatory design perspective-laymen to generate mid-air haptic sensations. We present the results of an end-user elicitation study yielding a user-defined set of mid-air haptic sensations to match gestures used for interacting with an Augmented Reality menu environment. In addition, we discuss the suitability of the end-user elicitation method to that end.

Mid-air haptic (MAH) feedback is an interesting means to provide augmented haptic feedback for gesture-based technology as it enables a sense of touch without physical contact with an actuator. Although quite some work already investigated the user experience (UX) of MAH feedback during initial encounter, we are not aware of studies testing the UX after repeated use, with regard to both pragmatic and hedonic UX, as well as emotional reactions. In this study, we tested how the UX of MAH feedback changed over the course of five weeks by collecting both questionnaire as well as interview data of 31 participants. Our results showed that MAH feedback significantly increased the enjoyment, engagement, valence and arousal of the emotional response. However, the added value of valence was due to a novelty effect as it was only significantly elevated during initial use, and not after repeated use. Interestingly, the added value of MAH feedback in terms of enjoyment, engagement and arousal remained elevated over the course of five weeks. Moreover, the interview data hinted at substantial individual differences underlying the global trends from the questionnaire data, showing the importance of combining quantitative and qualitative data when testing the UX of MAH feedback.

Mid-air haptics is an emerging technology that can produce a sense of touch in mid-air using ultrasound. While the use of mid-air haptics has a lot of potential in various domains such as automotive, virtual reality or professional healthcare, we suggest that the home is an equally promising domain for such applications. We organized an ideation workshop with 15 participants preceded by a sensitizing phase to identify possible applications for mid-air haptics within the home. From the extensive set of ideas that resulted from this, five themes emerged: guidance, confirmation, information, warning and changing status. As general 'application categories', we propose that they can provide a useful basis for the future design and development of mid-air haptic applications in the home, and possibly also beyond. 1

Algorithmic recommender systems are on the rise in various societal domains, including journalism. While they offer great promise by making useful selections of large content pools, they raise various ethical and societal concerns due to their alleged lack of transparency, diversity and agency. Especially in the news context, this has serious implications because access to information is crucial in democratic societies. In this article we empirically explore the idea of algorithmic recommender personae as a productive socio-technical solution to these problems. We present the results from a two-phased qualitative study with Dutch and Belgian news readers (N ¼ 27) to 1) co-design potential news recommender personae by inductively discerning core news reading motivations and relevant features, and 2) evaluate the most promising personae on their usefulness. Results highlight three distinct recommender personae (Expert, Challenger and Unwinder) that correspond with news consumers' most salient reading motivations. We conclude that, in an increasingly automated future, allowing users more control and including them when designing recommender systems is key. With this study we hope that media organizations take up the challenge towards developing human-centered and responsible algorithmic systems that serve the public good.