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High Force Sensing Accuracy in Piezoelectric Based Interactive Displays by Artificial Neural Networks

Gao, S; Duan, J; Wei, Z; Nathan, A; (2018) High Force Sensing Accuracy in Piezoelectric Based Interactive Displays by Artificial Neural Networks. SID Symposium Digest of Technical Papers , 49 (1) pp. 1893-1896. 10.1002/sdtp.12443. Green open access

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Abstract

Over panel stress non‐uniformity strongly limits the detection accuracy of piezo based force sensing in interactive displays. In this work, nested artificial neural networks based technique is presented to address the issue of stress non‐uniformity. High detection accuracy in terms of touch position and force amplitude is demonstrated by the proposed technique.

Type: Article
Title: High Force Sensing Accuracy in Piezoelectric Based Interactive Displays by Artificial Neural Networks
Event: SID
Location: Los Angeles
Dates: 21 May 2018 - 25 May 2018
Open access status: An open access version is available from UCL Discovery
DOI: 10.1002/sdtp.12443
Publisher version: http://dx.doi.org/10.1002/sdtp.12443
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Interactive display, piezoelectric touch panel, force sensing, artificial neural networks
UCL classification: UCL > Provost and Vice Provost Offices
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/10051357
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