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High Three-Dimensional Detection Accuracy in Piezoelectric-Based Touch Panel in Interactive Displays by Optimized Artificial Neural Networks

1
School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100083, China
2
Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100083, China
3
Electronic & Electrical Engineering Department, University College London, London WC1E 7JE, UK
4
Cicada Canada Inc., Toronto, ON l5v1t7, Canada
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(4), 753; https://doi.org/10.3390/s19040753
Received: 7 January 2019 / Revised: 28 January 2019 / Accepted: 31 January 2019 / Published: 13 February 2019
(This article belongs to the Section Physical Sensors)
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Abstract

High detection accuracy in piezoelectric-based force sensing in interactive displays has gained global attention. To achieve this, artificial neural networks (ANN)—successful and widely used machine learning algorithms—have been demonstrated to be potentially powerful tools, providing acceptable location detection accuracy of 95.2% and force level recognition of 93.3% in a previous study. While these values might be acceptable for conventional operations, e.g., opening a folder, they must be boosted for applications where intensive operations are performed. Furthermore, the relatively high computational cost reported prevents the popularity of ANN-based techniques in conventional artificial intelligence (AI) chip-free end-terminals. In this article, an ANN is designed and optimized for piezoelectric-based touch panels in interactive displays for the first time. The presented technique experimentally allows a conventional smart device to work smoothly with a high detection accuracy of above 97% for both location and force level detection with a low computational cost, thereby advancing the user experience, and serviced by piezoelectric-based touch interfaces in displays. View Full-Text
Keywords: piezoelectric-based touch panel; force sensing; detection accuracy; interactive displays; artificial neural network piezoelectric-based touch panel; force sensing; detection accuracy; interactive displays; artificial neural network
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Gao, S.; Dai, Y.; Kitsos, V.; Wan, B.; Qu, X. High Three-Dimensional Detection Accuracy in Piezoelectric-Based Touch Panel in Interactive Displays by Optimized Artificial Neural Networks. Sensors 2019, 19, 753.

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