Wrist-Powered Touch: Evaluating Smartwatch-Based Touch Gesture Recognition for Interaction in Extended Reality

Abstract

The lack of tactile feedback and occlusion from visual tracking systems hinders touch interaction in Extended Reality (XR) environments. In this work, we present a method that enables touch gesture interaction on any physical surface using smartwatch-based inertial sensing. By using accelerometer data from a smartwatch, our approach captures micro-wrist movements to detect seven distinct touch gestures with 91.67% accuracy via a Long Short-Term Memory neural network. Our approach allows users to interact with XR interfaces anchored to everyday surfaces, such as tables or walls, while benefting from natural haptic feedback. We introduce a dataset collected from 20 participants to demonstrate the feasibility through a controlled study. Our fndings show that smartwatch sensing ofers a low-cost, mobile, and accurate solution for extending XR input capabilities beyond the camera’s view on physical surfaces, paving the way for more natural and privacy-preserving interaction in future XR systems.

Publication
In Proceedings of Mensch und Computer 2025