Around-device finger input on commodity smartwatches with learning guidance through discoverability
Bibliographic Data
| ID | 21642434 |
|---|---|
| Authors | Marium-E- Jannat (0000-0002-4815-4741, University of British Columbia, corresponding author), Xing-Dong Yang (0000-0002-6732-6748, Simon Fraser University), Khalad Hasan (0009-0006-2890-5460, University of British Columbia) |
| Year | 2023 |
| Volume | 179 |
| Pages | 103105 |
| Publication date | 2023-11-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International Journal of Human-Computer Studies (JOURNAL) |
| Journal identifiers | ISSN: 1071-5819 • E-ISSN: 1095-9300 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ijhcs.2023.103105 |
| OpenAlex | W4383315608 |
| Language | EN |
| Citations received | 1 |
| References cited | 9 |
User interactions with smartwatches are limited due to one-finger usage on small touch screens. However, smartwatch interaction capabilities can be extended beyond the screen into the around-device space by leveraging multi-finger interactions. In this paper, we explore suitable finger postures and gestures in mid-air and on the back of the palm to extend interaction capabilities on the unmodified commodity smartwatch while ensuring their learnability through discoverability. We conduct a design study to find a set of finger postures and gestures suitable for interacting with off-the-shelf smartwatches. An application is then designed to detect the posture-gesture set with on-device dual cameras while examining their classification accuracy. To facilitate learnability through discoverability of the gesture-posture set, we explore ‘context-aware-hints’ that shows a sub-set of gesture-posture and their associated actions based on the usage context. Results from a user study show that the guidance helps users to discover and learn them quickly and accurately
Computer vision · Discoverability · Embedded system · Gesture · Human–computer interaction · Interaction technique · Learnability · Smartwatch · Stylus · Wearable computer · Computer Science · Gaze Tracking and Assistive Technology · Hand Gesture Recognition Systems · Interactive and Immersive Displays · Artificial Intelligence
| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |