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User-Oriented Piezoelectric Force Sensing and Artificial Neural Networks in Interactive Displays

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. Green open access

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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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