TapSkin: Recognizing on-skin input for smartwatches
Abstract:
The touchscreen has been the dominant input surface for smartphones and smartwatches. However, its small size compared to a phone limits the richness of the input gestures that can be supported. We present TapSkin, an interaction technique that recognizes up to 11 distinct tap gestures on the skin around the watch using only the inertial sensors and microphone on a commodity smartwatch. An evaluation with 12 participants shows our system can provide classification accuracies from 90.69% to 97.32% in three gesture families - number pad, d-pad, and corner taps. We discuss the opportunities and remaining challenges for widespread use of this technique to increase input richness on a smartwatch without requiring further on-body instrumentation.
Año de publicación:
2016
Keywords:
- Machine learning
- Inertial sensing
- Smartwatch interaction
- Acoustic sensing
- Input technology
Fuente:
![scopus](/_next/image?url=%2Fscopus.png&w=128&q=75)
Tipo de documento:
Conference Object
Estado:
Acceso restringido
Áreas de conocimiento:
- Ciencias de la computación
Áreas temáticas:
- Métodos informáticos especiales