WRIST

Watch-Ring Interaction and Sensing Technique for Wrist Gestures and Macro-Micro Pointing





Abstract: To better explore the incorporation of pointing and gesturing into ubiquitous computing, we introduce WRIST, an interaction and sensing technique that leverages the dexterity of human wrist motion. WRIST employs a sensor fusion approach which combines inertial measurement unit (IMU) data from a smartwatch and a smart ring. The relative orientation difference of the two devices is measured as the wrist rotation that is independent from arm rotation, which is also position and orientation invariant. Employing our test hardware, we demonstrate that WRIST affords and enables a number of novel yet simplistic interaction techniques, such as (i) macro-micro pointing without explicit mode switching and (ii) wrist gesture recognition when the hand is held in different orientations (e.g., raised or lowered). We report on two studies to evaluate the proposed techniques and we present a set of applications that demonstrate the benefits of WRIST. We conclude with a discussion of the limitations and highlight possible future pathways for research in pointing and gesturing with wearable devices.

Keywords: Smartwatch; wrist gesture; distal pointing; large displays

Appeared:

  • - Hui-Shyong Yeo, Juyoung Lee, Hyung-il Kim, Aakar Gupta, Andrea Bianchi, Daniel Vogel, Hideki Koike, Woontack Woo, and Aaron Quigley. 2019. WRIST: Watch-Ring Interaction and Sensing Technique for Wrist Gestures and Macro-Micro Pointing. In Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI '19). Association for Computing Machinery, New York, NY, USA, Article 19, 1–15. DOI:https://doi.org/10.1145/3338286.3340130