Abstract: We present empirical insights into modeling touch input performance, in terms of time and offset to targets, using Gaussian models and a cross-validation framework based on prediction coverage and bias of z-scores with log-likelihood analysis. Our results, from data collected from seven participants with upper-body motor impairments, indicate an optimum window of 8 to 24 touch observations before models plateau in performance. We interpret our findings through the lens of ability-based design, and propose a four-step procedure—observe, model, revise, and share—for implementing touch targets adaptive to users’ motor abilities. The procedure is lightweight, requiring only basic numerical computations of touch time and offset measurements available on all platforms, making it readily deployable across a variety of touchscreen devices.

Conference: CHI EA ’26: Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems, April 13 – 17, 2026

Publication: Association for Computing Machinery, New York, NY,  United States

Link: https://dl.acm.org/doi/proceedings/10.1145/3772363

Abstract: This article presents empirical findings from a study with eleven users with upper-body motor impairments, who imagined input devices and corresponding gestures for performing common tasks in interactive systems. Results show a strong preference for embodied devices, primarily integrated with the hands, and identify ten device archetypes, with smartphones and remote controls being the most frequently envisioned. The study also reveals substantial variability in gesture design, with minimal agreement across participants, reflecting diverse motor abilities. Based on these insights, the authors propose design recommendations grounded in ability-based and ability-mediating design, and outline future directions for imagination-driven accessible computing.

Authors: Radu-Daniel Vatavu, Ovidiu-Ciprian Ungurean

Conference: CHI 2026 – Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems

Publication: Association for Computing Machinery (ACM), New York, NY, USA

Link: https://doi.org/10.1145/3772318.3790437 

Abstract: Haptic feedback, commonly experienced as vibrotactile cues on mobile devices, increases user performance and enhances user experience, but research addressing users with upper-body motor impairments remains scarce. In particular, variations in how touch input is performed across different motor abilities raise questions about the optimal location, on-device or on-body, for vibrotactile feedback to maximize its effectiveness. In this work, we apply design thinking to explore alternative approaches for delivering haptic feedback at locations distant from the on-screen touch point, such as the user’s hand, wrist, forearm, or even the other arm. To inform our design explorations, we leverage empirical findings from a dataset of touch gestures performed on mobile devices by users with various upper-body motor impairments. We present future research opportunities at the intersection of haptic technology, wearable devices, accessible computing, and touchscreen input.

Conference: 2025 Conference on Creativity and Cognition (C&C ’25)

Publication: Association for Computing Machinery, New York, NY, USA, 409–413

Link: https://doi.org/10.1145/3715336.3735691

WOS:001543736500041

Abstract: The emergence of AI-powered UI generation tools presents both opportunities and challenges for accessible design, but their ability to produce truly accessible outcomes remains underexplored. In this work, we examine the effects of different prompt strategies through an evaluation of ninety interfaces generated by two AI tools across three application domains. Our findings reveal that, while these tools consistently achieve basic accessibility compliance, they rely on homogenized design patterns, which can limit their effectiveness in addressing specialized user needs. Through interviews with eight professional designers, we examine how this standardization impacts creativity and challenges the design of inclusive UIs. Our results contribute to the growing discourse on AI-powered design with (i) empirical insights into the capabilities of AI tools for generating accessible UIs, (ii) identification of barriers in this process, and (iii) guidelines for integrating AI into design workflows in ways that support both designers’ creativity and design flexibility.

Authors: Alexandra-Elena Guriță, Radu-Daniel Vatavu

Conference: 2025 ACM Designing Interactive Systems Conference (DIS ’25)

Publication: Association for Computing Machinery, New York, NY, USA, 1197–1209

Link: https://doi.org/10.1145/3715336.3735691

Abstract: We introduce Gesture-A11Y, a large-scale, web-based hub serving as a searchable database and tool to assist researchers and practitioners in identifying gestures that align with the abilities and preferences of users experiencing visual or motor disabilities. Gesture-A11Y is the result of an eight-year-long research effort, during which we collected over 22,000 records of touch, motion, on-wheelchair, and on-body gestures performed by users with various abilities, along with their preferences of gesture input across various devices and contexts of use. We offer Gesture-A11Y as an open-source tool to drive more accessible and inclusive gesture interaction design.

Authors: Mihail Terenti, Laura-Bianca Bilius, Ovidiu-Ciprian Ungurean, Radu-Daniel Vatavu

Conference: W4A ’25, the 22nd International Web for All Conference

Publication: ACM, New York, NY, USA, 2025

Recognitions: Recipient of the Accessibility Challenge Judges Award

Link: https://dx.doi.org/10.1145/3744257.3744280

Abstract: Understanding end-user performance with gesture input is essential for designing intuitive and effective interactions. Unfortunately, open gesture datasets are scarce, in particular those addressing users with impairments, which hinders advancements in accessible and inclusive user interface design for devices and applications featuring gesture interactions. To address this, we introduce Gesture-A11Y, a web-based tool with a large database aimed to help identify gestures aligning with users’ abilities and preferences. Gesture-A11Y offers access to over 22,000 records of touchscreen, mid-air, on-body, and on-wheelchair gestures performed by users with various visual and/or motor abilities, along with their preferences and perceptions of gesture input across different mobile and wearable devices.

Authors: Mihail Terenti, Laura-Bianca Bilius, Ovidiu-Ciprian Ungurean, Radu-Daniel Vatavu

Conference: W4A ’25, the 22nd International Web for All Conference

Publication: ACM, New York, NY, USA

Recognition: Awarded the Best Communication Paper prize.

Link: https://dx.doi.org/10.1145/3744257.3744267

Abstract: The integration of Large Language Models (LLMs) into web development workflows has the potential to revolutionize user interface design, yet their ability to produce accessible interfaces still remains underexplored. In this paper, we present an evaluation of LLM-generated user interfaces against the accessibility criteria from the Web Content Accessibility Guidelines (WCAG 2.1), comparing the output of ChatGPT and Claude with two distinct prompt types—accessibility-agnostic and accessibility-oriented. Our evaluation approach, consisting of automated testing, expert evaluation, and LLM self-reflection, reveals that accessibility-oriented prompts increase success counts and reduce violation rates in WCAG criteria, but persistent barriers remain, particularly in semantic structure. We argue that advancing accessible user interface development through LLM-generated code requires not just enhanced prompting but deeper semantic understanding and context awareness in these systems. We use our findings to suggest future work opportunities.

Authors: Alexandra-Elena Gurita, Radu-Daniel Vatavu

Conference: W4A ’25, the 22nd International Web for All Conference. ACM, New York, NY, USA

Link: https://dx.doi.org/10.1145/3744257.3744266

Abstract: Disponibilitatea recentă a instrumentelor de generare a interfețelor de utilizator bazate pe inteligență artificială impune o înțelegere clară a capacității acestora de a produce designuri accesibile, conforme cu standardele stabilite. În acest scop, această lucrare prezintă rezultatele unei evaluări a cincizeci de interfețe generate cu ajutorul a cinci instrumente publice de design bazate pe AI, comparate în raport cu criteriile WCAG 2.1 (de exemplu, contrastul textului și dimensiunea țintelor de interacțiune), folosind atât prompturi generale, cât și prompturi axate pe accesibilitate. Analiza noastră relevă un nivel moderat de severitate a încălcărilor (𝑀=0.47) pe o scară de la 0 (niciuna) la 4 (critic), cu contrastul textului (𝑀=1.08) și dimensiunea țintelor (𝑀=0.86) ca principale probleme, dar ușor de remediat. Contrar așteptărilor noastre, prompturile orientate spre accesibilitate nu au îmbunătățit conformitatea, ci au redus-o (𝑀=0.54 față de 𝑀=0.39). Totuși, trei dintre instrumentele analizate au arătat rezultate mai bune prin dialog și rafinări iterative.

Authors: Alexandra-Elena Gurita, Radu-Daniel Vatavu

Conference: ACM Web Conference 2025 (WWW Companion ’25) April 28-May 2, 2025, Sydney, NSW, Australia

Publication: ACM, New York, NY, USA

Link: https://dl.acm.org/doi/10.1145/3701716.3715552

WOS:001527543600158 / A*-rank conference according to ARC CORE 

Abstract: What happens when we prompt AI to create “bad” design? To find out, we challenged four AI-driven design tools to create user interfaces that explicitly violate established accessibility criteria, only to discover them as prisoners of their usability-oriented training. This finding raises a critical question: How can we develop AI that understands accessibility deeply enough to know when to comply and when to thoughtfully challenge established design principles? Through systematic attempts to subvert AI tools and make them follow our request, we found them both rigid and limited: capable of reproducing accessible patterns, but incapable of thoughtful deviation when context demanded it. By adopting the lens of intentional inaccessibility as an investigation method, we raise questions about the nature of design intelligence that demand reconsideration of how design knowledge is integrated into AI-driven design tools.

Authors: Alexandra-Elena Gurita, Radu-Daniel Vatavu

Conference: CHI Conference on Human Factors in Computing Systems

Publication: Association for Computing Machinery, New York, NY, USA, Article 624, 1–7

Link: https://doi.org/10.1145/3706599.3716220

Abstract: In this study we examine the user experience of distal haptics for touchscreen input through confirmatory vibrations of on-screen touches at various on-body locations. To this end, we introduce the Distal Haptics Continuum, a conceptual framework of haptic feedback delivery across the body, organized along the dimensions of Body Laterality and Proximity to the touch point. Our results, from three experiments involving 45 participants and 16 locations across the hand, arm, and whole body, reveal a strong preference for distal haptics over no haptics at all, despite the spatial decoupling from the touch point, with the index finger yielding the highest user experience. We also identify additional on-body locations—the adjacent fingers, wrist, and abdomen—that unlock distinctive design opportunities. Building on our insights, demonstrating haptics effectiveness even when distant from the touch point, we outline implications for integrating various on-body locations, well beyond the index finger, into the user experience of touchscreen input.

Authors: Mihail Terenti, Radu-Daniel Vatavu

Conference: CHI Conference on Human Factors in Computing Systems 2025 (CHI ’25)

Publication: Association for Computing Machinery, New York, NY, USA, Article 500, 1–19

Link: https://doi.org/10.1145/3706598.3713474

WOS:001501406100055 / A*- rank conference according to ARC CORE