Expanding Touch Interaction Capabilities for Smart-rings: An Exploration of Continual Slide and Microroll Gestures

Abstract

As smart-rings emerge in both research and commercial markets, their limited physical size remains to restrict the interaction potential and input vocabulary possible. Thus, focusing on touch interaction for its natural and preferred input potential, this early work explores the combination of slide and microroll gestures performed by the thumb in continual motion on a smart-ring's touch capacitive surface. We first capture over 3000 slide and microroll gesture instances, extract features, and generate and test machine learning models that are able to discern the slide and microroll gestures within the same touch instance. Through the use of 18 features, our Random Forest model provides a 92.4% accuracy. We conclude with demonstrations of potential applications utilizing continual slide and microroll gestures, and a short discussion which provides future research directions stemming from the positive results obtained from this preliminary work.