Do-It-Yourself (DIY) approaches to assistive technology (AT) design offer promising opportunities for personalization and user empowerment. However, the technical complexity of digital fabrication tools continues to pose significant barriers for many AT makers, limiting broader adoption. This study explores the potential of generative AI (GenAI) to help overcome these challenges in DIY-AT design and fabrication. We developed an AI-assisted interface combining text-to-image and image-to-3D generation and evaluated it with 18 DIY-AT makers, including clinicians and technical designers, through design workshops. During these sessions, makers created and refined AT concepts, with data collected via think-aloud protocols and semi-structured interviews. The findings indicated that GenAI sparked creativity, lowered technical barriers, and supported AT personalization, especially for makers with limited design experience. However, several concerns emerged, including the generation of one-size-fits-all solutions, lack of disability-specific training data, limited accessibility features, vocabulary mismatches in clinical settings, and overall trust in AI-generated outputs. We reflect on these findings to inform the development of future AI-fabrication tools, identifying three key directions: (1) addressing data bias and accessibility gaps in AI systems, (2) expanding accessibility through inclusive interface design and diverse input modalities, and (3) reframing GenAI as a creative partner that supports disability-centered AT design and customization. Acknowledging the limitations of current AI systems, this study underscores the potential of the GenAI-assisted interface to expand access to DIY-AT, particularly for makers with diverse abilities and non-technical backgrounds.

This paper presents the development of an open-source platform that enables assistive technology (AT) makers without prior design experience to easily create customized 3D models of common AT devices for activities of daily living. The platform leverages simplified parametric modeling to support users with varying skill levels in adapting devices to meet the specific needs of end-users. By providing an open-source, web-based design tool to the broader maker community, including individuals with disabilities, caregivers, clinicians, and educators, this study aims to democratize access to adaptive AT creation by lowering design barriers and promoting inclusive participation. The platform features an intuitive interface and an expandable library of models, offering a scalable foundation for personalized AT customization. Ongoing efforts include iterative refinement, expanding the model library, and conducting evaluations across diverse user groups and settings to advance the tool and prepare it for widespread adoption.

This paper investigates the motivations, practices, and functional adaptations within DIY prosthetic-making communities. We analyze 80 publicly shared prosthetic artifacts across open-source platforms and 26 maker-generated videos from global creators. Through inductive thematic analysis and artifact coding, we identify six key motivational categories: comfort and adaptation, functional empowerment, aesthetic integration, emotional healing, task-specific design, and cost reduction. Our findings highlight how users and caregivers modify or build prosthetics not only to regain physical ability but also to reclaim agency, express identity, and adapt to specific life scenarios. Together, these findings illustrate how grassroots innovation reimagines prosthetic design as a space for creativity, community exchange, and resistance to one-size-fits-all approaches. This study contributes to accessibility research by deepening our understanding of user-driven prosthetic design and demonstrating how personal fabrication tools empower people with disabilities to address complex needs often overlooked by clinical and commercial systems.

This paper examines the potential integration of generative AI into the assistive technology (AT) making and adaptation process, with Occupational Therapists (OTs) as the primary beneficiaries, as they are often involved in designing ‘do-it-yourself assistive technology’ (DIY AT) to support independent living for individuals with disabilities. We initiated the study by considering the traditional AT-making processes performed by OTs and prototyped a web interface that incorporates generative AI to support these processes. Through a series of user studies, we collected OTs' preliminary insights on how generative AI could bridge the gap between clinical reasoning and technical design, potentially streamlining the AT creation and adaptation process while maintaining the crucial element of personalized AT solutions. The study's findings highlight several key benefits of generative AI in OT practice: 1) customization of AT solutions tailored to individual client needs, 2) improved visualization capabilities for client communication, 3) inspiration for new AT design ideas, and 4) potential for rapid prototyping and practice. However, key drawbacks were noted, including limitations in inputting measurements, which can lead to inaccurate outputs and necessitate substantial modifications to the created AT, along with challenges associated with the current state of generative AI.

This paper aims to showcase the feasibility of a proof-of-concept parametric software that empowers occupational therapists (OTs) in fabricating customized adaptations of assistive technologies (ATs) to effectively address the distinctive requirements of individuals with hand impairments. The platform enables OTs to modify pre-designed models of utensil grips, serving as examples of ATs, based on individuals' hand assessments and anthropometric data. We conducted observations and interviews to gain insights into the AT adaptation processes by OTs for individuals with hand impairments. Subsequently, using an iterative design process, we created an interface prototype that allows for customized adaptations of ATs and invited an OT to participate in the preliminary testing of the prototype. We provide an outline of the design requirements for parametric modeling tools intended to assist OTs and other clinicians in creating personalized ATs for individuals facing constrained hand motor abilities.

Instant messengers (IMs) have created an unprecedented shift in interpersonal communication. This study explores how users reappropriate instant messengers, their motivations, and the associated factors behind this behavior. We conducted a survey, with 81 responses, and interviewed 14 participants to understand the unexpected ways instant messengers are used for purposes beyond communication, focusing on how they are used for Personal Information Management (PIM). We used an iterative process of open-coding and affinity diagramming to reveal three key themes: users' reappropriation of messaging technologies for saving, remembering, and transferring information; users' struggles and strategies to find information buried in conversations; and users' emotional attachments and attitudes about keeping and deleting this data. Our study reveals informality and accessibility as the primary motivators for reappropriating IMs and examines how this repurposing behavior connects to privacy, digital possessions, and lifelogging.

We designed Augmenta11y, a cross-platform application that aims to provide ubiquitous reading and learning companionship to children with dyslexia. This paper presents the iterative user-centered design process and implementation details of the application and offers suggestions and guidelines for designing future assisted reading applications. We foresee the opportunity for Augmenta11y to be an accessible, low-cost assistive reading solution for dyslexic children with little to no access to educational specialists or after-school practices. The Augmenta11y application is available on iOS and Android.

Insulin pumps are effective tools for the precise control of glucose levels, for type 1 diabetes (T1D) patients. Unfortunately, many design and usability challenges still exist with these technologies. We investigated current shortcomings and limitations through survey (N=105), interview (N=7), and participatory workshop (N=3) data collection methods. Our findings revealed issues with current technolog y including wear-ability and accessibility in public, operation while performing demanding tasks, interruptions during social activities, continuity of maintenance, and interface operations. Using the data from our investigative work, we produced design criteria to develop a novel wrist-worn interface and separate pump design for a closed loop system. We then evaluated the design through remote usability testing sessions (N=7) with insulin pump users. Our study aspires to inform the future design of novel insulin pumps that enable people with T1D to maintain better control of their glucose through consistent interactions with these tools, during their everyday activities.

In this Pictorial we explain and describe Eclipse, a method aimed at eliciting subjective qualities of people's experiences of and relationships with public places. Our method guides participants to sequentially explore their memories, sensations, sense of place, and stories related to a public place. Our goal is to present this method in a pictorial form to make it more concise and more easily usable by other interaction designers; in this, we want to depict the richness and qualities of the elicitations, and ultimately the subjective qualities of a public place.