Momona Yamagami

Kai Malcolm, César Uribe, Momona Yamagami

Invasive and non-invasive neural interfaces hold promise as high-bandwidth input devices for next-generation technologies. However, neural signals inherently encode sensitive information about an individual's identity and health, making data sharing for decoder training a critical privacy challenge. Federated learning (FL), a distributed, privacy-preserving learning framework, presents a promising solution, but it remains unexplored in closed-loop adaptive neural interfaces. Here, we introduce FL-based neural decoding and systematically evaluate its performance and privacy using high-dimensional electromyography signals in both open- and closed-loop scenarios. In open-loop simulations, FL significantly outperformed local learning baselines, demonstrating its potential for high-performance, privacy-conscious neural decoding. In contrast, closed-loop user studies required adapting FL methods to accommodate single-user, real-time interactions, a scenario not supported by standard FL. This modification resulted in local learning decoders surpassing the adapted FL approach in closed-loop performance, yet local learning still carried higher privacy risks. Our findings highlight a critical performance-privacy tradeoff in real-time adaptive applications and indicate the need for FL methods specifically designed for co-adaptive, single-user applications.

Momona Yamagami, Kelly Mack, Jennifer Mankoff et al.

Many individuals with disabilities and/or chronic conditions (da/cc) experience symptoms that may require intermittent or on-going medical care. However, healthcare is an often-overlooked domain for accessibility work, where access needs associated with temporary and long-term disability must be addressed to increase the utility of physical and digital interactions with healthcare workers and spaces. Our work focuses on a specific domain of healthcare often used by individuals with da/cc: physical therapy (PT). Through a twelve-person interview study, we examined how people's access to PT for their da/cc is hampered by social (e.g., physically visiting a PT clinic) and physiological (e.g., chronic pain) barriers, and how technology could improve PT access. In-person PT is often inaccessible to our participants due to lack of transportation and insufficient insurance coverage. As such, many of our participants relied on at-home PT to manage their da/cc symptoms and work towards PT goals. Participants felt that PT barriers, such as having particularly bad symptoms or feeling short on time, could be addressed with well-designed technology that flexibly adapts to the person's dynamically changing needs while supporting their PT goals. We introduce core design principles (adaptability, movement tracking, community building) and tensions (insurance) to consider when developing technology to support PT access. Rethinking da/cc access to PT from a lens that includes social and physiological barriers presents opportunities to integrate accessibility and adaptability into PT technology.

Momona Yamagami, Sasa Junuzovic, Mar Gonzalez-Franco et al.

Virtual Reality (VR) applications often require users to perform actions with two hands when performing tasks and interacting with objects in virtual environments. Although bimanual interactions in VR can resemble real-world interactions -- thus increasing realism and improving immersion -- they can also pose significant accessibility challenges to people with limited mobility, such as for people who have full use of only one hand. An opportunity exists to create accessible techniques that take advantage of users' abilities, but designers currently lack structured tools to consider alternative approaches. To begin filling this gap, we propose Two-in-One, a design space that facilitates the creation of accessible methods for bimanual interactions in VR from unimanual input. Our design space comprises two dimensions, bimanual interactions and computer assistance, and we provide a detailed examination of issues to consider when creating new unimanual input techniques that map to bimanual interactions in VR. We used our design space to create three interaction techniques that we subsequently implemented for a subset of bimanual interactions and received user feedback through a video elicitation study with 17 people with limited mobility. Our findings explore complex tradeoffs associated with autonomy and agency and highlight the need for additional settings and methods to make VR accessible to people with limited mobility.