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:

scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Ciencias de la computación

Áreas temáticas:

  • Métodos informáticos especiales