Patrick Parzer, Adwait Sharma, Anita Vogl, Jürgen Steimle, Alex Olwal, Michael Haller
2017 Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology - UIST '17  
c d e f Figure 1 : SmartSleeve is a wearable textile that can detect 2D surface and 2.5D deformation gestures, like twist (a). We use an unobtrusive and robust sewn-based connection (b), which withstands high deformation gestures (c). The force distribution values of the gestures (d) are further processed for real-time classification with a hybrid gesture detection algorithm (e) to control a media player (f), for example. ABSTRACT Over the last decades, there have been numerous efforts in
more » ... le computing research to enable interactive textiles. Most work focus, however, on integrating sensors for planar touch gestures, and thus do not fully take advantage of the flexible, deformable and tangible material properties of textile. In this work, we introduce SmartSleeve, a deformable textile sensor, which can sense both surface and deformation gestures in real-time. It expands the gesture vocabulary with a range of expressive interaction techniques, and we explore new opportunities using advanced deformation gestures, such as, Twirl, Twist, Fold, Push and Stretch. We describe our sensor design, hardware implementation and its novel non-rigid connector architecture. We provide a detailed description of our hybrid gesture detection pipeline that uses learning-based algorithms and heuristics to enable real-time gesture detection and tracking. Its modular architecture allows us to derive new gestures through the combination with continuous properties like pressure, location, and direction. Finally, we report on the promising results from our evaluations which demonstrate real-time classification.
doi:10.1145/3126594.3126652 dblp:conf/uist/ParzerSVSOH17 fatcat:fuawav5jjbcfjpirburhd7kg7u