Researchers have demonstrated a proof-of-concept way to control augmented reality (AR) apps with deliberate changes to normal walking—such as ordering a café latte, adjusting music, or answering a call. The system recognized gestures in the reported study, but this was an experimental AR-headset interface, not a consumer feature ready for everyday use.
What are gait gestures?
Gait gestures are intentional foot movements that alter a person’s ordinary walking pattern and serve as commands. Rather than tapping a screen or making an exaggerated dance-like motion, a user makes a defined change to their step while continuing to walk. The idea extends foot-operated controls—such as car pedals—to the way people move on foot.
“There’s a long history of using feet to control machines,” said Ching-Yi Tsai, the study’s lead author and a former visiting scholar at the University of Waterloo’s David R. Cheriton School of Computer Science. “For example, the pedals on the car, but very little research has been done into using the way we walk as an input for a device.” The statement was quoted by New Atlas.
How the AR interface was developed
According to the New Atlas report, researchers first considered 22 possible time-based foot gestures. In an initial evaluation involving 25 participants, they assessed whether candidate movements fitted naturally into walking, how easy they were to perform, and whether people would feel comfortable using them in public. They then selected seven gestures for a follow-up proof-of-concept AR-headset interface.
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That selection reflects a design trade-off: a movement must be recognizable, but it also needs to remain practical and socially unobtrusive. Daniel Vogel, a University of Waterloo professor of computer science, described why extreme gestures were not necessarily good candidates:
“Extreme movements like dance steps or a jump would likely be easy for a system to recognize, but these might be harder to perform, and they would deviate too far from normal walking for people to feel comfortable doing them in public,” Vogel said. “We didn’t want users to feel like someone from Monty Python’s Ministry of Silly Walks!”
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The quote and study details above are attributed to New Atlas.
What participants did—and what the 92% figure means
In the reported proof of concept, participants wore an AR headset and performed tasks while walking. They used the interface to play a song, adjust its volume, order a café latte, and accept or decline an incoming phone call. New Atlas reports an overall gesture-recognition accuracy of 92% and says participants generally found the technology easy to use, responded positively, and indicated they would use it again.
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The 92% figure describes recognition in the reported research setting. It does not establish that the system would achieve the same result amid the varied pace, terrain, footwear, distractions, and movement patterns of routine public use. The source does not provide enough methodological detail to generalize that result to everyday performance.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the demonstration does—and does not—show
- It shows: A small set of walking-pattern changes can serve as commands in a research AR-headset interface for music, a café order, and call handling.
- It does not show: That the interface is a released consumer feature, works with a particular retail headset, or has demonstrated long-term performance in ordinary settings. The report names no headset manufacturer or model.
- It highlights: Gesture design must balance fit with walking, ease of movement, social acceptability, and recognizability—not maximize recognition alone.
The work is described in a New Atlas report published January 16, 2025, which identifies the University of Waterloo as the source institution and says the study appeared in the ACM Symposium on User Interface Software and Technology (UIST) 2024 proceedings. The original proceedings paper is not separately consulted here, so the study details and figures are attributed to that report.
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