The 色色研究所 has been selected as one of six recipients worldwide in Meta Reality Labs鈥 competitive research program exploring the future of muscle-based human鈥揷omputer interaction. The award supports a new interdisciplinary research effort led by Kyle Reed, professor in the Department of Mechanical and Aerospace Engineering, in collaboration with Michael Morris, a philosopher of technology and associate professor in the Department of Philosophy.
The project focuses on motor learning, specifically how people learn to detect, refine, and gain voluntary control over subtle muscle signals that are often produced without visible movement. By studying how these normally unnoticed muscle activations can be reinforced during everyday activities, the research aims to advance fundamental understanding of how humans acquire new motor skills and how muscle-based signals might enable more expressive, high-bandwidth interaction with technology. The work uses electromyography (EMG), a technique that measures small electrical signals generated by muscles even when no visible motion occurs.
Rather than relying on short, structured training sessions, the project explores motor learning as a continuous, real-world process. Participants wear EMG sensors during daily life, and feedback is delivered only when relevant muscle activity naturally emerges. This approach allows researchers to study how motor control develops organically over time, providing insights into how people adapt to new forms of interaction and how learning can be supported without explicit instruction or repetitive practice.
The envisioned ethics collaboration is multi-directional. On one hand, it applies established ethical standards and best practices to the research design and data collection required for the experiments. At the same time, the collaboration draws on specific features of the studies to raise broader questions about the moral significance of human鈥揷omputer interaction. Building on discussions in cognitive science and phenomenology, Reed and Morris aim to develop a framework for articulating both the promise and the potential pitfalls of emerging HCI technologies, particularly as they relate to the first-person experience of attention and autonomy.
鈥淭his project is fundamentally about how people learn new ways of controlling their bodies,鈥 said Reed. 鈥淏y understanding motor learning at this level, we can help shape future muscle-based interfaces that feel intuitive, empowering, and aligned with human values.鈥
While the research is fundamentally focused on motor learning and interaction, these questions are also relevant in contexts where motor control is altered, such as after stroke. Many individuals with stroke retain subtle muscle activity even when voluntary control is limited, making stroke a compelling setting for studying how motor learning principles operate. By examining how people learn to detect and strengthen these signals, the project connects foundational motor learning research with real-world challenges involving impaired motor control.
Meta鈥檚 research program supports exploratory work examining how muscle-based interfaces could enable richer, more natural interactions between humans and technology, while accounting for individual preferences and real-world contexts. USF鈥檚 project contributes to this effort by combining motor learning science, engineering, and ethics in a single, integrated framework.
More information about Meta鈥檚 call for research proposals can be found here:
https://www.meta.com/blog/reality-labs-emg-call-for-research-proposals/