Premium
P‐193: High Force Sensing Accuracy in Piezoelectric Based Interactive Displays by Artificial Neural Networks
Author(s) -
Gao Shuo,
Duan Jifang,
Wei Zhicheng,
Nathan Arokia
Publication year - 2018
Publication title -
sid symposium digest of technical papers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 44
eISSN - 2168-0159
pISSN - 0097-966X
DOI - 10.1002/sdtp.12443
Subject(s) - artificial neural network , position (finance) , piezoelectricity , computer science , amplitude , stress (linguistics) , artificial intelligence , acoustics , physics , optics , finance , economics , linguistics , philosophy
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.