Gao, S;
Duan, J;
Kitsos, V;
Selviah, D;
Nathan, A;
(2018)
User-Oriented Piezoelectric Force Sensing and Artificial Neural Networks in Interactive Displays.
IEEE Journal of the Electron Devices Society
, 6
pp. 766-773.
10.1109/JEDS.2018.2848917.
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Abstract
Force touch based interactivity has been widely integrated into displays equipped in most of smart electronic systems such as smartphones and tablets. This paper reports on application of artificial neural networks to analyze data generated from piezoelectric based touch panels for providing customized force sensing operation. Based on the experimental results, high force sensing accuracy (93.3%) is achieved when three force levels are used. Two-dimensional sensing, also achieved with the proposed technique, with high detection accuracy (95.2%). The technique presented here not only achieves high accuracy, but also allows users to define the range of force levels through behavioral means thus enhancing interactivity experience.
Type: | Article |
---|---|
Title: | User-Oriented Piezoelectric Force Sensing and Artificial Neural Networks in Interactive Displays |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1109/JEDS.2018.2848917 |
Publisher version: | https://doi.org/10.1109/JEDS.2018.2848917 |
Language: | English |
Additional information: | Copyright © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/ redistribution requires IEEE permission. 766 See http://www.ieee.org/ publications_standards/ publications/rights/index.html for more information |
Keywords: | Artificial neural network, customized force sensing, detection accuracy, interactive display |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/10051363 |




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