WristDial: An Eyes-Free Integer-Value Input Method by Quantizing the Wrist Rotation

ABSTRACT

Smartwatches are a convenient substitute for smartphones in hand-busy situations, but there is limited interactivity to one-handed use of wrist-worn devices. In this paper, we propose WristDial, a one-handed integer input technique which uses quantization of the angular distance of the wrist rotation with nonvisual feedback. Using tactile feedback, we present four techniques based on counting of tactile stimuli. With one of them, 94.44% average accuracy and 2.81 s average completion time were acquired in the task of entering a number from the range 1 to 10. We also evaluate the quantitative performance of the combination of interruptible speech and non-speech auditory feedback. Our results show that when speech feedback exists, adding a continuous change of pitch or clicking sound at the boundaries does not have a significant effect on the performance. Using only speech feedback, 95.47% accuracy and 1.45 s completion time were acquired.

Additional information

Funding

This research was supported by Next-Generation Information Computing Development Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT [2017M3C4A7065963].

Notes on contributors

Eunhye Youn

Eunhye Youn received a B.S. degree in electronic engineering and computer science from Sungkyunkwan University and an M.S. degree in computer science from KAIST. She is currently a Ph.D. candidate at the HCI Lab, School of Computing, KAIST. Her research interests include interaction devices and interaction techniques for wearable computers.

Sangyoon Lee

Sangyoon Lee received his B.S. and M.S. degrees in computer science from the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea, in 2016 and 2018, respectively. He is currently pursuing a Ph.D. degree at the School of Computer Science, KAIST, Daejeon, Korea. His current research interests include human–computer interaction.

Sunbum Kim

Sunbum Kim received his B.S. and M.S. degrees in computer science from the Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea, in 2017 and 2019, respectively. He is currently pursuing a Ph.D. degree at the School of Computing, KAIST, Daejeon, Korea. His current research interests include human–computer interaction.

Youngbo Aram Shim

Youngbo Aram Shim received a B.S. degree in bio and brain engineering and computer science and a M.S. degree in computer science from KAIST. He is currently a Ph.D. candidate in the HCI Lab, School of Computing, KAIST. His research interests include haptic interface design and implementation for entertainment.

Liwei Chan

Liwei Chan is an Associate Professor of National Yang Ming Chiao Tung University in Taiwan. He received his PhD from National Taiwan University and had been an Assistant Professor at Keio University in Japan. His main research area is Human-Computer Interaction.

Geehyuk Lee

Geehyuk Lee received BS and MS degrees in physics from KAIST, and a PhD degree in electrical engineering from University of Pennsylvania. He is currently a professor in the School of Computing, KAIST. His primary research interests are interaction devices and techniques for smart devices, wearable computers, and smart environments.