Humans and industrial collaborative robots (cobots) form intricate relationships as they both possess agency, share spaces, and must coordinate effectively to work together. In initial interactions, much like human-team dynamics, the perceived contribution of each agent plays a crucial role in shaping the collaborative experience and the acceptance of cobots. Beyond unilateral support perceptions from or to the cobot—termed as Received Support (RS) and Given Support (GS)—Mutual Support (MS) embodies a balanced, reciprocal dynamic where humans view their contribution as equal to that of the cobot. Drawing from social knowledge in human teams and aligning with recent interpretations of human-robot interactions, we propose that perceiving MS can foster fluent, trusting, and harmonious collaboration, ultimately increasing cobot acceptance in work routines. In this observational study, 56 novices collaborated with the industrial cobot UR10e to assess support dynamics. We explored how perceptions of balanced (MS) or unbalanced support (RS and GS) impact task performance (i.e., task time), Cognitive Factors (COG-F), User Experience (UX-F), and Human-Robot Relationship Factors (HRR-F), ultimately influencing cobot acceptance. We also examined the influence of initial attitudes toward robots. The findings suggest that fostering perceptions of MS, rather than focusing solely on functionality or work relief (RS), can lead to smoother integration and greater acceptance of cobots, especially among novices, regardless of their initial attitudes toward robots.

In recent years, Augmented Reality (AR) technology has permeated various domains. This paper focuses on the critical aspect of enhancing customer interaction within AR e-commerce environments by investigating the impact of virtual product size manipulation on usability, user experience, and shopping satisfaction. We tested two manipulation modalities: an unconstrained scaling modality, enabling users to manually adjust product dimensions, and an assisted modality providing automatic 1:1 scaling. Using the Microsoft HoloLens 2 AR headset, we engaged 40 participants with small and large virtual products in shopping scenarios using these two manipulation modalities. Results show that users found the automatic manipulation modality to provide a superior user experience, being more effective, easy, useful, and pleasant when interacting with large virtual products. For small virtual products, they expressed a preference for free manipulation. Customer satisfaction with the shopping experience is positive, however, product size and manipulation modality affect the repatronage intention. The findings offer insights into designing AR e-commerce interfaces, highlighting that providing different manipulation modalities depending on the size of the products allows for enriching the shopping experience and improving the AR market potential.

The increasingly aging workforce is bringing particular attention to senior individuals in production sectors. While the interest in Virtual Reality (VR) applications for industrial robotics grows, the question of whether and how senior workers can withstand VR-based repetitive tasks arises. We here aimed to answer such questions by systematically assessing young and senior users’ experiential, behavioural, and cognitive factors during simulated robotic teleoperations in VR. Two control systems for VR telerobotics, button- and action-based controls, were employed. Human performance, vigilance, and workload were measured through self-reports and a VR-integrated eye-tracker. Additionally, age-dependent differences in individual cultural and experiential factors were explored via self-report measures. Despite being slower and experiencing increased fatigue under specific conditions, as suggested by the eye-tracking measures, senior users demonstrated comparable precision in operating the robotic arm to their younger counterparts. Notably, both age groups reported similar levels of perceived fatigue. The paper provides an in-depth analysis of the advantages and challenges of adopting advanced telerobotics control systems across different age groups, consistently emphasising the human-centered dimension.

COVID-19 had substantial effects on the IoT community which designs systems for safety: the urge to face masks worn by everyone, the analysis of crowds to avoid the spread of the disease, and the sanitization of public environments has led to exceptional research acceleration and fast engineering of the related solutions. Now that the pandemic is losing power, some applications are becoming less important, while others are proving to be useful regardless of the criticality of COVID-19. The Safe Place project is a prime example of this situation (DATE23 MPP category: final stage). Safe Place is an Italian 3M euro regional industrial/academic project, financed by European funds, created to ensure a multidisciplinary choral reaction to COVID-19 in critical environments such as rest homes and public places. Safe Place consortium was able to understand what is no longer useful in this post-pandemic period, and what instead is potentially attractive for the market. For example, the detection of face masks has little importance, while sanitization does have much. This paper shares such analysis, which emerged through a co-design process of three public Safe Place project demonstrators, involving heterogeneous figures spanning from scientists to lawyers.

Virtual Reality (VR) is gaining ground in the robotics and teleoperation industry, opening new prospects as a novel computerized methodology to make humans interact with robots. In contrast with more conventional button-based teleoperations, VR allows users to use their physical movements to drive robotic systems in the virtual environment. The latest VR devices are also equipped with integrated eye-tracking, which constitutes an exceptional opportunity for monitoring users’ workload online. However, such devices are fairly recent, and human factors have been consistently marginalized so far in telerobotics research. We thus covered these aspects by analyzing extensive behavioral data during simulated guidance of an industrial robot in VR through a pick-and-place task. Users drove the robot via button-based and action-based controls and under low (single-task) and high (dual-task) mental demands. We collected self-reports, performance and eye-tracking data. Specifically, we asked i) how the interactive features of VR affect users’ performance and workload, and additionally tested ii) the sensibility of diverse eye parameters in monitoring users’ vigilance and workload throughout the task. Users performed faster and more accurately, while also showing a lower mental workload, when using an action-based VR control. Among the eye parameters, pupil size was the most resilient indicator of workload, as it was highly correlated with the self-reports and was not affected by the user's degree of physical motion in VR. Our results bring a fresh human-centric overview of human-robot interactions in VR, and systematically demonstrate the potential of VR devices for monitoring human factors in telerobotics contexts.

The possibility that common users are successfully recruited in cyberattacks represents a considerable vulnerability because it implies that citizens can legitimize cyberattacks instead of condemning them. We propose to adopt an argumentative approach to identify which premises allow such legitimization. To showcase this approach, we created four short narratives describing cyberattacks involving generic users and covering different motives for the attacks: profit, recreation, revenge, and ideology. A sample of 16 participants read the four narratives and was afterward interviewed to express their position on the attacks described. All interview transcripts were then analyzed with an argumentative approach, and 15 premises were found to account for the different positions taken. We describe the premises, their distribution across the four narratives, and discuss the implications of this approach for cybersecurity.

A valid Human-Robot Interaction (HRI) should be effective for the majority of the population. However, gender, gaming experience, or other individual factors are often likely to affect users' performance when interacting with a robot. In the present study, we measured the performance and perceived workload of participants driving a robot through a pick-and-place task in Virtual Reality (VR) via controller buttons or physical actions. The following individual factors were considered in the analysis: gaming experience, gender, learnability skills, problem solving and trust in technology. Results showed that all the accounted individual factors impacted either performance or perceived demand, but only when guiding the robot via controller buttons. Our findings foster the adoption of more natural ways of teleoperating robots, such as by physical actions, as they demonstrated to be exempt from the influence of individual factors, and are likely to be effective for a broader section of the population.

Virtual Reality (VR) technologies are widely employed to investigate human behavior in dangerous situations that cannot be safely reproduced in the real world, allowing researchers to study in an ecological way complex scenarios such as training for risky jobs, safety procedures, emergencies and, more recently, moral dilemmas in driving context. Understanding how people act when facing severe accidents involving unavoidable collisions has extremely important implications for the design and development of the “decisional system” of Autonomous Vehicles (AV s). However, previous studies have not focused on the differences between being the driver acting in a complex moral situation or being in a self-driving car that chooses for you. In the present paper, we described a case study that uses a first-person virtual reality simulation to investigate people's emotional reactions, perceived sense of responsibility, and acceptability of moral behavior in human and autonomous driving modalities. The main findings showed that participants experienced a high sense of presence in our simulation and react differently to the two driving conditions, showing a greater arousal, a more negative valence, and an increased sense of responsibility when faced moral dilemmas as drivers. Instead, in scenarios that did not involve killing someone (non-moral dilemmas), being in a fully autonomous vehicle was judged less pleasant than being the actual driver. These results suggest that people prefer to be in control only in common driving situations and not when their actions have deadly consequences on other people, suggesting the need to consider emotional factors in studying decision-making applied to autonomous vehicles, as a mean to reach a more complete understanding of people's reactions to this new technology, and to possibly gain insights for the design of autonomous driving systems and, more generally, AI-driven machines.

Computerized solutions in the domain of creativity and expressive performance increasingly provide art and artists with exciting new opportunities. However, the combination of automation and creativity also raises controversies and resistance in some user groups. This paper considers the case of software-generated visuals in live music performance and tries to make sense of the ambivalent response given by its intended users (i.e., DJs and VJs). We carried out seven face-to-face interviews, an online survey (N = 102) and 25 interviews at a distance to unravel DJs' and VJs' positions on automated visual software. Four core controversies were eventually identified, gravitating around the implications of using such software on DJs' and VJs' identities as artists and on their competitive advantage in their activity sector. The conclusions reconnect these findings with the larger issue of understanding the users' responses to automation.

The use of implicit relevance feedback from neurophysiology could deliver effortless information retrieval. However, both computing neurophysiologic responses and retrieving documents are characterized by uncertainty because of noisy signals and incomplete or inconsistent representations of the data. We present the first-of-its-kind, fully integrated information retrieval system that makes use of online implicit relevance feedback generated from brain activity as measured through electroencephalography (EEG), and eye movements. The findings of the evaluation experiment (N = 16) show that we are able to compute online neurophysiology-based relevance feedback with performance significantly better than chance in complex data domains and realistic search tasks. We contribute by demonstrating how to integrate in interactive intent modeling this inherently noisy implicit relevance feedback combined with scarce explicit feedback. Although experimental measures of task performance did not allow us to demonstrate how the classification outcomes translated into search task performance, the experiment proved that our approach is able to generate relevance feedback from brain signals and eye movements in a realistic scenario, thus providing promising implications for future work in neuroadaptive information retrieval (IR).

Conversations among people involve solving disputes, building common ground, and reinforce mutual beliefs and assumptions. Conversations often require external information that can support these human activities. In this paper, we study how a spoken conversation can be supported by a proactive search agent that listens to the conversation, detects entities mentioned in the conversation, and proactively retrieves and presents information related to the conversation. A total of 24 participants (12 pairs) were involved in informal conversations, using either the proactive search agent or a control condition that did not support conversational analysis or proactive information retrieval. Data comprising transcripts, interaction logs, questionnaires, and interviews indicated that the proactive search agent effectively augmented the conversations, affected the conversations' topical structure, and reduced the need for explicit search activity. The findings also revealed key challenges in the design of proactive search systems that assist people in natural conversations.

While ordinary touchscreen-based interfaces on urban explorer applications draw much of a user's attention onto the screen, visual and audio-haptic augmented reality interfaces have emerged as the two main streams for enabling direct focus on the surroundings. However, neither interface alone satisfies users in the highly dynamic urban environment. This research investigates how the two complementary augmentation can coexist on one system and how people adapt to the situation by selecting the more suitable interface. A prototype was deployed in a field experiment in which participants explored points of interest in an urban environment with both interfaces. The engagement with the surroundings was compared with a touchscreen-based application. Most participants spontaneously switched between the two interfaces, which manifests the value of the availability of both interfaces on one system. The results point at the situated advantages of either interface and reveal the users' preferences when both interfaces are available.

In this paper, we propose a novel method, based on keystroke dynamics, to distinguish between fake and truthful personal information written via a computer keyboard. Our method does not need any prior knowledge about the user who is providing data. To our knowledge, this is the first work that associates the typing human behavior with the production of lies regarding personal information. Via experimental analysis involving 190 subjects, we assess that this method is able to distinguish between truth and lies on specific types of autobiographical information, with an accuracy higher than 75%. Specifically, for information usually required in online registration forms (e.g., name, surname and email), the typing behavior diverged significantly between truthful or untruthful answers. According to our results, keystroke analysis could have a great potential in detecting the veracity of self-declared information, and it could be applied to a large number of practical scenarios requiring users to input personal data remotely via keyboard.

We present a preliminary design study for utilizing eye tracking to support interacting with a multi-document visualization. Complex information seeking tasks can involve collection and comparison of multiple documents, resulting in long and sustained search sessions. The sustained and evolving nature of the session also provides the search interface the opportunity to gather information on the user state and interaction history, which can be used to adapt the information content and representation. We designed a system to evaluate how eye tracking information can be used for adapting the visual salience of information entities. The interface features documents and related keywords that are arranged in a radial layout configuration called the intent radar. Reading history and visual attention, as registered by eye tracking data, are respectively used to trace read items and for visual cueing. We evaluated the interface with 16 participants to gather subjective feedback about specific components and features of the interface. The overall results show that the interface and gaze-related appearance of keywords was positively received by the users.

Previous research investigated how to leverage the new type of social data available on the web, e.g., tags, ratings and reviews, in recommending and personalizing information. However, previous works mainly focused on predicting ratings using collaborative filtering or quantifying personalized ranking quality in simulations. As a consequence, the effect of social information in user's information search and information-selection behavior remains elusive. The objective of our research is to investigate the effects of social information on users’ interactive search and information-selection behavior. We present a computational method and a system implementation combining different graph overlays: social, personal and search-time user input that are visualized for the user to support interactive information search. We report on a controlled laboratory experiment, in which 24 users performed search tasks using three system variants with different graphs as overlays composed from the largest publicly available social content and review data from Yelp: personal preferences, tags combined with personal preferences, and tags and social ratings combined with personal preferences. Data comprising search logs, questionnaires, simulations, and eye-tracking recordings show that: 1) the search effectiveness is improved by using and visualizing the social rating information and the personal preference information as compared to content-based ranking. 2) The need to consult external information before selecting information is reduced by the presentation of the effects of different overlays on the search results. Search effectiveness improvements can be attributed to the use of social rating and personal preference overlays, which was also confirmed in a follow-up simulation study. With the proposed method we demonstrate that social information can be incorporated to the interactive search process by overlaying graphs representing different information sources. We show that the combination of social rating information and personal preference information improves search effectiveness and reduce the need to consult external information. Our method and findings can inform the design of interactive search systems that leverage the information available on the social web.

Smart glasses suffer from obtrusive or cumbersome interaction techniques. Studies show that people are not willing to publicly use, for example, voice control or mid-air gestures in front of the face. Some techniques also hamper the high degree of freedom of the glasses. In this paper, we derive design principles for socially acceptable, yet versatile, interaction techniques for smart glasses based on a survey of related work. We propose an exemplary design, based on a haptic glove integrated with smart glasses, as an embodiment of the design principles. The design is further refined into three interaction scenarios: text entry, scrolling, and point-and-select. Through a user study conducted in a public space we show that the interaction technique is considered unobtrusive and socially acceptable. Furthermore, the performance of the technique in text entry is comparable to state-of-the-art techniques. We conclude by reflecting on the advantages of the proposed design.

Augmented Reality (AR) browsers show geo-referenced data in the current view of a user. When the amount of data grows too large, the display quickly becomes cluttered. Clustering items by spatial and semantic attributes can temporarily alleviate the issue, but is not effective against an increasing amount of data. We present an adaptive information density display for AR that balances the amount of presented information against the potential clutter created by placing items on the screen. We use hierarchical clustering to create a level-of-detail structure, in which nodes closer to the root encompass groups of items, while the leaf nodes contain single items. Our method selects items and groups from different levels of this hierarchy based on user-defined preferences and on the amount of visual clutter caused by placing these items. The number of presented items is adapted during user interaction to avoid clutter. We compare our interface to a conventional AR browser interface in a qualitative user study. Users clearly preferred our interface, because it provided a better overview of the data and allowed for easier comparison. In a second study, we evaluated the effect of different degrees of clustering on search and recall tasks. Users generally made fewer errors, when using our interface for a search task, which indicates that the reduced clutter allowed them to stay focused on finding the relevant items.

Persuasive Technology (PT) is an interdisciplinary research field that focuses on the design and development of technologies aimed at changing users[#x02019] attitudes or behaviors through persuasi...

Interactive systems are increasingly used in a growing number of domains to encourage users to perform certain actions or take a certain position toward a given subject. This article offers a perspective on interactive persuasive systems that emphasizes theories and concepts that can guide their design and evaluation. The goal is not to champion a theoretical model over others or to compare the effectiveness of different persuasive strategies but rather to depict the current conceptual landscape in this field and highlight emerging concepts and positions that have recently appeared in it. The article includes a discussion of some representative, general, and domain-specific constructs that can be used to evaluate the effectiveness of interactive persuasive systems.

Locating points of interest (POIs) in cities is typically facilitated by visual aids such as paper maps, brochures, and mobile applications. However, these techniques require visual attention, which ideally should be on the surroundings. Non-visual techniques for navigating towards specific POIs typically lack support for free exploration of the city or more detailed guidance. To overcome these issues, we propose a multimodal, wearable system for alerting the user of nearby recommended POIs. The system, built around a tactile glove, provides audio-tactile cues when a new POI is in the vicinity, and more detailed information and guidance if the user expresses interest in this POI. We evaluated the system in a field study, comparing it to a visual baseline application. The encouraging results show that the glove-based system helps keep the attention on the surroundings and that its performance is on the same level as that of the baseline.

Advanced interactive visualization such as in virtual environments and ubiquitous interaction paradigms pose new challenges and opportunities in considering real-time responses to subliminal cues. In this paper, we propose a synthetic reality platform that, combined with psychophysiological recordings, enables us to study in realtime the effects of various subliminal cues. We endeavor to integrate various aspects known to be relevant to implicit perception. The context is of consumer experience and choice of an artifact where the generation of subliminal perception through an intelligent 3D interface controls the spatio-temporal aspects of the information displayed and of the emergent narrative. One novel contribution of this work is the programmable nature of the interface that exploits known perceptive phenomena (e.g. masking, crowding and change blindness) to generate subliminal perception.

In this paper we describe the results of a controlled study of a social game, Magpies, which was built on the Facebook Online Social Network (OSN) and enhanced with contextual social information in the form of a variety of social network indices. Through comparison with a concurrent control trial using an identical game without the enhanced social information, it was shown that the additional contextual data increased the frequency of social activity between players engaged in the game. Despite this increase in activity, there was little increase in growth of the player-base when compared to the control condition. These findings corroborate previous work that showed how socio-contextual enhancement can increase performance on task-driven games, whilst also suggesting that it can increase activity and engagement when provided as context for non task-driven game environments.

Mobile devices such as the iPhone provide state of the art interaction capabilities also for web browser applications. Our mobile development is targeted to a Energy Awareness application that provides playful access to detailed and realtime information on energy consumption of appliances of a household. Using the available Safari Browser that adopts W3C web standards we demonstrate the implementation of a 3D carousel giving access to cards on a web page where each card gives access to information on one appliance. The carousel can be browsed using the multitouch capability of the iPhone. We describe the programming approach and discuss the lesson learned in developing the touch interaction with the carousel.