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

被引：17
|
作者：
Gao, Shuo [1 ]
Duan, Jifang [2 ]
Kitsos, Vasileios [2 ]
Selviah, David R. [2 ]
Nathan, Arokia [3 ]
机构：
[1] Beihang Univ, Sch Instrumentat Sci & Optoelect Engn, Beijing 100083, Peoples R China
[2] UCL, Elect & Elect Engn Dept, London WC1E 7JE, England
[3] Univ Cambridge, Elect Engn Dept, Cambridge CB3 0FA, England
来源：
IEEE JOURNAL OF THE ELECTRON DEVICES SOCIETY | 2018年 / 6卷 / 01期
关键词：
Artificial neural network; customized force sensing; detection accuracy; interactive display;
D O I：
10.1109/JEDS.2018.2848917
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
引用
收藏
页码：766 / 773
页数：8
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