Improving Low-Vision Chart Accessibility via On-Cursor Visual ContextDespite widespread use, charts remain largely inaccessible for Low-Vision Individuals (LVI). Reading charts requires viewing data points within a global context, which is difficult for LVI who may rely on magnification or experience a partial field of vision. We aim to improve exploration by providing visual access to critical context. To inform this, we conducted a formative study with five LVI. We identified four fundamental contextual elements common across chart types: axes, legend, grid lines, and the overview. We propose two pointer-based interaction methods to provide this context: Dynamic Context, a novel focus+context interaction, and Mini-map, which adapts overview+detail principles for LVI. In a study with N=22 LVI, we compared both methods and evaluated their integration to current tools. Our results show that Dynamic Context had significant positive impact on access, usability, and effort reduction; however, worsened visual load. Mini-map strengthened spatial understanding, but was less preferred for this task. We offer design insights to guide the development of future systems that support LVI with visual context while balancing visual load.2026YSYotam Sechayk et al.The University of TokyoVisual Impairment Technologies (Screen Readers, Tactile Graphics, Braille)Interactive Data VisualizationUncertainty VisualizationCHI
FontCraft: Multimodal Font Design Using Interactive Bayesian OptimizationCreating new fonts requires a lot of human effort and professional typographic knowledge. Despite the rapid advancements of automatic font generation models, existing methods require users to prepare pre-designed characters with target styles using font-editing software, which poses a problem for non-expert users. To address this limitation, we propose FontCraft, a system that enables font generation without relying on pre-designed characters. Our approach integrates the exploration of a font-style latent space with human-in-the-loop preferential Bayesian optimization and multimodal references, facilitating efficient exploration and enhancing user control. Moreover, FontCraft allows users to revisit previous designs, retracting their earlier choices in the preferential Bayesian optimization process. Once users finish editing the style of a selected character, they can propagate it to the remaining characters and further refine them as needed. The system then generates a complete outline font in OpenType format. We evaluated the effectiveness of FontCraft through a user study comparing it to a baseline interface. Results from both quantitative and qualitative evaluations demonstrate that FontCraft enables non-expert users to design fonts efficiently.2025YTYuki Tatsukawa et al.The University of Tokyo, Igarashi LabGraphic Design & Typography ToolsCustomizable & Personalized ObjectsCHI
The Walking Meditation Mat: Leveraging Targeted Heat Sensation to Guide Attention InwardWe present the walking meditation mat research, leveraging targeted heat to help meditators focus attention inward. The mat, measuring three meters in length, is designed with 10 visual signifiers and 10 corresponding heater pads arranged in a step-by-step pattern. Walking meditation is challenging, as it requires both inward and outward attention. In a qualitative study we studied the walking meditation experience with or without heat, evaluating the impact of the mat’s visual signifiers and the gentle feet-focused targeted heat during the walking experience. Our findings reveal the tension participants experience between external design factors and their internal meditation process. Visual signifiers were more commonly associated with outward attention, dizziness and imbalance, while targeted heat affordances were more commonly associated with attention to bodily sensations, calmness, grounding, and reflection. We conclude with insights regarding the role of targeted heat in balancing inward and outward attention in walking meditation and introspective processes.2025TDTamar Dublin et al.Reichman University, Media Innovation LabElectronic Textiles (E-textiles)Dance & Body Movement ComputingCHI
Somaesthetic Meditation Wearable: Exploring the Effect of Targeted Warmth Technology on Meditators' ExperiencesMindfulness meditation has vast benefits, yet is challenging for many. We designed a novel targeted warmth somaesthetic wearable and evaluated how the thermal sensation is perceived during meditation. In a qualitative study, twenty participants explored the wearable during meditation. Findings reveal participants' rich experiences, sensations, and feelings. They perceived the technology as an appropriate tool for self-exploration. Even when participants initially felt the wearable was distracting their meditation process, they easily learned how to leverage it in their introspection process. We report on four potential roles for warmth technology: functional (pulling focal of attention), behavioral (motivating to "get back to the practice"), emotional (comforting during the lonely process), and therapeutic feelings. We conclude with design guidelines, highlighting that warmth is a promising technology for meditation if designed to encourage self-exploration of body sensations and emotions while not compromising the natural meditation practice.2024TETalia Sofia Ezer et al.Reichman UniversityVibrotactile Feedback & Skin StimulationHaptic WearablesCHI
iPose: Interactive Human Pose Reconstruction from VideoReconstructing 3D human poses from video has wide applications, such as character animation and sports analysis. Automatic 3D pose reconstruction methods have demonstrated promising results, but failure cases can still appear due to the diversity of human actions, capturing conditions, and depth ambiguities. Thus, manual intervention remains indispensable, which can be time-consuming and require professional skills. We thus present iPose, an interactive tool that facilitates intuitive human pose reconstruction from a given video. Our tool incorporates both human perception in specifying pose appearance to achieve controllability, and video frame processing algorithms to achieve precision and automation. A user manipulates the projection of a 3D pose via 2D operations on top of video frames, and the 3D poses are updated correspondingly while satisfying both kinematic and video frame constraints. The pose updates are propagated temporally to reduce user workload. We evaluate the effectiveness of iPose with a user study on the 3DPW dataset and expert interviews.2024JLJingyuan Liu et al.The University of TokyoHuman Pose & Activity Recognition3D Modeling & AnimationCHI
A Social Approach for Autonomous Vehicles: A Robotic Object to Enhance Passengers’ Sense of Safety and TrustOne of the central challenges in designing autonomous vehicles concerns passenger trust and sense of safety. This challenge is related to passengers' well-established past experience with non-autonomous vehicles, which leads to concern about the absence of a driver. We explored whether it is possible to address this challenge by designing an interaction with a simple robotic object positioned on the vehicle's dashboard. We leveraged the automatic human tendency to interpret non-verbal robotic gestures as social cues and designed an interaction with the robot in the autonomous vehicle. The robotic object greeted the passenger, indicated that the vehicle was attentive to its surroundings, and informed the passenger that the drive was about to begin. We evaluated whether the robot's non-verbal behavior would provide the signals and social experience required to support passengers' trust and sense of safety. In an in-person (in-situ) experiment, participants were asked to enter an autonomous vehicle and take the time to decide if they were willing to go for a drive. As they entered the vehicle, the robot performed the designed behaviors. We evaluated the participants' considerations and experience while they made their decision. Our findings indicated that participants' trust ratings and safety-related experience were higher than those of a baseline group who did not experience the interaction with the robot. Participants also perceived the robot as providing companionship during a lonely experience. We suggest that robotic objects are a promising technology for enhancing passengers' experience in autonomous vehicles.2024SKSrivatsan Chakravarthi Kumaran et al.Automated Driving Interface & Takeover DesignIn-Vehicle Haptic, Audio & Multimodal FeedbackEye Tracking & Gaze InteractionHRI
The Effects of Observing Robotic Ostracism on Children's Prosociality and Basic NeedsResearch on robotic ostracism is still scarce and has only explored its effects on adult populations. Although the results revealed important carryover effects of robotic exclusion, there is no evidence yet that those results occur in child-robot interactions. This paper provides the first exploration of robotic ostracism with children. We conducted a study using the Robotic Cyberball Paradigm in a third-person perspective with a sample of 52 children aged between five to ten years old. The experimental study had two conditions: Exclusion and Inclusion. In the Exclusion condition, children observed a peer being excluded by two robots; while in the Inclusion condition, the observed peer interacted equally with the robots. Notably, even 5-year-old children could discern when robots excluded another child. Children who observed exclusion reported lower levels of belonging and control, and exhibited higher prosocial behaviour than those witnessing inclusion. However, no differences were found in children's meaningful existence, self-esteem, and physical proximity across conditions. Our user study provides important methodological considerations for applying the Robotic Cyberball Paradigm with children. The results extend previous literature on both robotic ostracism with adults and interpersonal ostracism with children. We finish discussing the broader implications of children observing ostracism in human-robot interactions.2024FCFilipa Correia et al.Social Robot InteractionEmpowerment of Marginalized GroupsHRI
The Power of Opening Encounters in HRI: How initial robotic behavior shapes the interaction that followsOpening encounters are a fundamental component of every interaction. Psychology research highlights the valence of opening encounters as one of the main factors that shape the nature of the interaction that follows. In this work, we evaluated whether opening encounters would have a similarly powerful effect on human-robot interactions. We tested how positive and negative opening encounters with a robot would impact the subsequent interaction. In the experiment, a robotic dog approached a participant in a waiting room. The robot performed gestures designed to communicate different valences of opening encounters under three conditions: Positive, Negative, or No opening encounter. To evaluate the impact on the subsequent interaction, we measured participants' willingness to comply with a help request presented by the robot and their overall perception of the robot. Objective and subjective measures indicated that most participants in the Positive opening encounter condition helped the robot and reported a positive overall perception. An opposite pattern emerged in the other two conditions. Almost none of the participants helped the robot, and the overall perception of the robot was negative. Our findings suggest that opening encounters with robots should be carefully considered and well-designed due to their profound impact on the interaction that follows.2024HEHadas Erel et al.Social Robot InteractionHuman-Robot Collaboration (HRC)HRI
Implications of AI Bias in HRI: Risks (and Opportunities) when Interacting with a Biased RobotSocial robotic behavior is commonly designed using AI algorithms which are trained on human behavioral data. This training process may result in robotic behaviors that echo human biases and stereotypes. In this work, we evaluated whether an interaction with a biased robotic object can increase participants’ stereotypical thinking. In the study, a gender-biased robot moderated debates between two participants (man and woman) in three conditions: (1) The robot’s behavior matched gender stereotypes (Pro-Man); (2) The robot’s behavior countered gender stereotypes (Pro-Woman); (3) The robot’s behavior did not reflect gender stereotypes and did not counter them (No-Preference). Quantitative and qualitative measures indicated that the interaction with the robot in the ProMan condition increased participants’ stereotypical thinking. In the No-Preference condition, stereotypical thinking was also observed but to a lesser extent. In contrast, when the robot displayed counter-biased behavior in the Pro-Woman condition, stereotypical thinking was eliminated. Our findings suggest that HRI designers must be conscious of AI algorithmic biases, as interactions with biased robots can reinforce implicit stereotypical thinking and exacerbate existing biases in society. On the other hand, counter-biased robotic behavior can be leveraged to support present efforts to address the negative impact of stereotypical thinking.2023THTom Hitron et al.Human-Robot Collaboration (HRC)Algorithmic Fairness & BiasTechnology Ethics & Critical HCIHRI
Humorous Robotic Behavior as a New Approach to Mitigating Social AwkwardnessSocial awkwardness is a frequent challenge to healthy social interactions and can dramatically impact how people feel, communicate and behave. It is known that humor can invoke positive feelings and enable people to modify perspective of a situation. We explored whether using a non-humanoid robotic object performing humorous behavior can reduce social awkwardness between two strangers. The robot was peripherally incorporated into the interaction to ensure the natural social flow. We compared the impact of humorous and non-humorous robotic gestures on the human-human interaction. Objective and subjective measures indicate that despite being peripheral to the human-human interaction, the humorous robotic gestures significantly reduced the intensity of awkwardness between the strangers. Our findings suggest humorous robotic behavior can be used to enhance interpersonal relationships hindered by awkwardness and still preserve natural human-human interaction.2023VPViva Sarah Press et al.Reichman University, Reichman UniversityAgent Personality & AnthropomorphismSocial Robot InteractionCHI
Field Evidence of the Effects of Privacy, Data Transparency, and Pro-social Appeals on COVID-19 App AttractivenessCOVID-19 exposure-notification apps have struggled to gain adoption. Existing literature posits as potential causes of this low adoption: privacy concerns, insufficient data transparency, and the type of appeal – collective- vs. individual-good – used to frame the app. As policy guidance suggests using tailored advertising to evaluate the effects of these factors, we present the first field study of COVID-19 contact tracing apps with a randomized, control trial of 14 different advertisements for CovidDefense, Louisiana’s COVID-19 exposure-notification app. We find that all three hypothesized factors -- privacy, data transparency, and appeals framing -- relate to app adoption, even when controlling for age, gender, and community density. Our results offer (1) the first field evidence supporting the use of collective-good appeals, (2) nuanced findings regarding the efficacy of data and privacy transparency, the effects of which are moderated by appeal framing and potential users’ demographics, and (3) field-evidence-based guidance for future efforts to encourage pro-social health technology adoption.2022SDSamuel Dooley et al.University of MarylandPrivacy by Design & User ControlPrivacy Perception & Decision-MakingCHI
Food Democracy in the Making: Designing with Local Food NetworksThis paper introduces the concept of ‘food democracy’ as a theoretical framing for HCI to engage in human-food interaction. Extending existing foci of health and environmental sustainability, food democracy requires thinking through aspects of social and economic justice, and democratic governance as directions for the study and design of technologies for alternative food movements. To exemplify food democracy, we report on field observations and interviews about the opportunities and challenges for supporting the development of local food networks with communities in deprived neighbourhoods using an online direct food marketing platform. Using a food democracy framing, we identify tensions around environmental, social, and economic goals; challenges of local food businesses operating within the existing economic paradigm; and differing perspectives on ownership and governance in the network. We discuss the need for HCI to design for systems change and propose a design space for HCI in supporting food democracy movements.2018SPSebastian Prost et al.Newcastle UniversitySustainable HCIFood Culture & Food InteractionCHI
Analysis and Modeling of Grid Performance on Touchscreen Mobile DevicesTouchscreen mobile devices can afford rich interaction behaviors but they are complex to model. Scrollable two-dimensional grids are a common user interface on mobile devices that allow users to access a large number of items on a small screen by direct touch. By analyzing touch input and eye gaze of users during grid interaction, we reveal how multiple performance components come into play in such a task, including navigation, visual search and pointing. These findings inspired us to design a novel predictive model that combines these components for modeling grid tasks. We realized these model components by employing both traditional analytical methods and data-driven machine learning approaches. In addition to showing high accuracy achieved by our model in predicting human performance on a test dataset, we demonstrate how such a model can lead to a significant reduction in interaction time when used in a predictive user interface.2018KPSean Peacock et al.Google Research & Machine Intelligence, Lancaster UniversityEye Tracking & Gaze InteractionInteractive Data VisualizationCHI