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Open AccessArticle

Intelligent RF-Based Gesture Input Devices Implemented Using e-Textiles

Department of Computer Science, University of Colorado Boulder, Boulder, CO 80309, USA
Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
Authors to whom correspondence should be addressed.
This paper is an extended version of our paper published in SwitchBack: An On-Body RF-based Gesture Input Device. In Proceedings of the 2014 ACM International Symposium on Wearable Computers, Seattle, WA, USA, 13–17 September 2014.
Academic Editors: Stefan Bosse, Ansgar Trächtler, Klaus-Dieter Thoben, Berend Denkena and Dirk Lehmhus
Sensors 2017, 17(2), 219;
Received: 1 December 2016 / Revised: 17 January 2017 / Accepted: 17 January 2017 / Published: 24 January 2017
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
We present an radio-frequency (RF)-based approach to gesture detection and recognition, using e-textile versions of common transmission lines used in microwave circuits. This approach allows for easy fabrication of input swatches that can detect a continuum of finger positions and similarly basic gestures, using a single measurement line. We demonstrate that the swatches can perform gesture detection when under thin layers of cloth or when weatherproofed, providing a high level of versatility not present with other types of approaches. Additionally, using small convolutional neural networks, low-level gestures can be identified with a high level of accuracy using a small, inexpensive microcontroller, allowing for an intelligent fabric that reports only gestures of interest, rather than a simple sensor requiring constant surveillance from an external computing device. The resulting e-textile smart composite has applications in controlling wearable devices by providing a simple, eyes-free mechanism to input simple gestures. View Full-Text
Keywords: e-textiles; wearable sensors; robotic materials e-textiles; wearable sensors; robotic materials
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Hughes, D.; Profita, H.; Radzihovsky, S.; Correll, N. Intelligent RF-Based Gesture Input Devices Implemented Using e-Textiles. Sensors 2017, 17, 219.

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