In virtual reality (VR) experiences, mismatches between reality and virtuality are usually undesirable, as they can disrupt immersion and induce cybersickness. However, when carefully controlled, they may expand the design space of VR. This research investigates perceptual detection thresholds for mismatches between real and virtual inclinations during cycling in VR. Using a custom simulation, N = 30 participants cycled through a virtual city while physical and visual inclinations were independently manipulated. Real inclinations were implemented with a tilting indoor bike, providing vestibular and proprioceptive feedback, while virtual inclinations within the simulated environment were presented visually. A multiple staircase procedure derived estimates for perceptual thresholds that approximate which mismatches in visual and physical inclination were still perceived as congruent. These thresholds reveal a window of perceived congruence before mismatches become noticeable to users. These findings advance understanding of sensory integration in VR cycling and inform applications in immersive training, exergames, and rehabilitation systems.

In the context of rising sedentary lifestyles, this paper investigates the efficacy of "Situated Artifacts"in promoting physical activity. We designed two artifacts that display users' physical activity data within their homes - one physical and one digital. We conducted a 9-week, counterbalanced, within-subject field study with N = 24 participants to assess the impact of these artifacts on physical activity, reflection, and motivation. We collected quantitative data on physical activity and administered daily and weekly questionnaires, employing individual Likert items and standardized instruments, as well as conducted interviews post-prototype usage. Our findings indicate that while both artifacts act as reminders for physical activity, the physical artifact was superior in terms of user engagement. The study revealed that this can be attributed to the higher perceived presence and, thereby, enhanced social interaction, which acts as a motivational source for activity. In this sense, situated artifacts gently nudge toward sustainable health behavior change.

We present a sensory substitution-based method for representing locations of remote objects in 3D space via haptics. By imitating auditory localization processes, we enable vibrotactile localization abilities similar to those of some spiders, elephants, and other species. We evaluated this concept in virtual reality by modulating the vibration amplitude of two controllers depending on relative locations to a target. We developed two implementations applying this method using either ear or hand locations. A proof-of-concept study assessed localization performance and user experience, achieving under 30° differentiation between horizontal targets with no prior training. This unique approach enables localization by using only two actuators, requires low computational power, and could potentially assist users in gaining spatial awareness in challenging environments. We compare the implementations and discuss the use of hands as ears in motion, a novel technique not previously explored in the sensory substitution literature.

Despite their ubiquity, bicycles remain largely unexplored as a space for personalization and cyclist-aware solutions. Since cycling is inherently a behavioral activity, we investigate its potential as a biometric trait for continuous identification and personalization. For this, we mounted multiple sensors on a regular bicycle and conducted an outdoor experiment (N = 16) across two sessions on two cycling tracks: a short, controlled track and a long, in-the-wild setup. This design enabled us to examine how stable cycling patterns are across sessions and how well individuals can be distinguished in controlled versus real-world conditions. Our findings demonstrate the feasibility of leveraging cycling behavior for continuous identification and personalization, achieving identification accuracies of up to 94.3%. We discuss the implications of these results for real-world deployment, as well as the challenges posed by environmental factors, rider variability, and the need for robust and unobtrusive sensing solutions.

Electrical Muscle Stimulation (EMS) has unique capabilities that can manipulate users’ actions or perceptions, such as actuating user movement while walking, changing the perceived texture of food, and guiding movements for a user learning an instrument. These applications highlight the potential utility of EMS, but such benefits may be lost if users reject EMS. To investigate user acceptance of EMS, we conducted an online survey (N = 101). We compared eight scenarios, six from HCI research applications and two from the sports and health domain. To gain further insights, we conducted in-depth interviews with a subset of the survey respondents (N = 10). The results point to the challenges and potential of EMS regarding social and technological acceptance, showing that there is greater acceptance of applications that manipulate action than those that manipulate perception. The interviews revealed safety concerns and user expectations for the design and functionality of future EMS applications.

Virtual mirrors displaying weight changes can support users in forming healthier habits by visualizing potential future body shapes. However, these often come with privacy, feasibility, and cost limitations. This paper introduces the Magic Mirror, a novel distortion-based mirror that leverages curvature effects to alter the appearance of body size while preserving privacy. We constructed the Magic Mirror and compared it to a video-based alternative. In an online study ( N =115), we determined the optimal parameters for each system, comparing weight change visualizations and manipulation levels. Afterward, we conducted a laboratory study ( N =24) to compare the two systems in terms of user perception, motivational potential, and willingness to use daily. Our findings indicate that the Magic Mirror surpasses the video-based mirror in terms of suitability for residential application, as it addresses feasibility concerns commonly associated with virtual mirrors. Our work demonstrates that mirrors that display weight changes can be implemented in users’ homes without any cameras, ensuring privacy.

The global COVID-19 pandemic created a constant need for hand disinfection. While it is still essential, disinfection use is declining with the decrease in perceived personal risk (e.g., as a result of vaccination). Thus this work explores using different visual cues to act as reminders for hand disinfection. We investigated different public display designs using (1) paper-based only, adding (2) screen-based, or (3) projection-based visual cues. To gain insights into these designs, we conducted semi-structured interviews with passersby (N=30). Our results show that the screen- and projection-based conditions were perceived as more engaging. Furthermore, we conclude that the disinfection process consists of four steps that can be supported: drawing attention to the disinfection station, supporting the (subconscious) understanding of the interaction, motivating hand disinfection, and performing the action itself. We conclude with design implications for technology-supported disinfection.

Nowadays, deep learning models enable numerous safety-critical applications, such as biometric authentication, medical diagnosis support, and self-driving cars. However, previous studies have frequently demonstrated that these models are attackable through slight modifications of their inputs, so-called adversarial attacks. Hence, researchers proposed investigating examples of these attacks with explainable artificial intelligence to understand them better. In this line, we developed an expert tool to explore adversarial attacks and defenses against them. To demonstrate the capabilities of our visualization tool, we worked with the publicly available CIFAR-10 dataset and generated one-pixel attacks. After that, we conducted an online evaluation with 16 experts. We found that our tool is usable and practical, providing evidence that it can support understanding, explaining, and preventing adversarial examples.