When language is used as a medium for sensory information—as when one describes a scene in words—a kind of virtual reality emerges: realities projected into the same sentence become virtual/equivalent. We call this Linguistic VR (LVR). LVR is constituted by codes shaped chiefly by majority cultural norms. In today’s world—where AI, largely built on linguistic data and processes, is deeply entangled with the everyday mediation of sensory information—it is necessary to critically re-examine the virtuality of this VR.

Human environments are physically supported by floors, which prevent people and furniture from gravitational pull. Since our body motions continuously generate vibrations and loads that propagate into the ground, measurement of these expressive signals leads to unobtrusive activity sensing. In this study, we present Flexel, a modular floor interface for room-scale tactile sensing. By paving a room with floor interfaces, our system can immediately begin to infer touch locations, track user locations, recognize foot gestures, and detect object locations. Through a series of exploratory studies, we determined the preferable hardware design that adheres to construction conventions, as well as the optimal sensor density that mediates the trade-off between cost and performance. We summarize our findings into design guidelines that are generalizable to other floor interfaces. Finally, we provide example applications for room-scale tactile sensing enabled by our Flexel system.