TapSkin: Recognizing On-Skin Input for Smartwatches

被引:41
|
作者
Zhang, Cheng [1 ]
Bedri, Abdelkareem [1 ]
Reyes, Gabriel [1 ]
Bercik, Bailey [1 ]
Inan, Omer T. [1 ]
Starner, Thad E. [1 ]
Abowd, Gregory D. [1 ]
机构
[1] Georgia Inst Technol, Atlanta, GA 30332 USA
关键词
Smartwatch interaction; acoustic sensing; inertial sensing; machine learning; input technology;
D O I
10.1145/2992154.2992187
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:13 / 22
页数:10
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