Find in Library
Search millions of books, articles, and more
Indexed Open Access Databases
User-Oriented Piezoelectric Force Sensing and Artificial Neural Networks in Interactive Displays
oleh: Shuo Gao, Jifang Duan, Vasileios Kitsos, David R. Selviah, Arokia Nathan
Format: | Article |
---|---|
Diterbitkan: | IEEE 2018-01-01 |
Deskripsi
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.