User-Oriented Piezoelectric Force Sensing and Artificial Neural Networks in Interactive Displays
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 customi...
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| Veröffentlicht in: | IEEE journal of the Electron Devices Society 2018-01, Vol.6, p.766-773 |
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| container_title | IEEE journal of the Electron Devices Society |
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| creator | Gao, Shuo Duan, Jifang Kitsos, Vasileios Selviah, David R. Nathan, Arokia |
| description | 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. |
| doi_str_mv | 10.1109/JEDS.2018.2848917 |
| format | Article |
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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%). 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| source | IEEE Open Access Journals; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals |
| subjects | Accuracy Artificial neural network Artificial neural networks customized force sensing Detection detection accuracy Displays Electrical engineering Electron devices Electronic systems Force interactive display Neural networks Object recognition Piezoelectric materials Piezoelectricity Sensors Smartphones Tablet computers Touch control panels |
| title | User-Oriented Piezoelectric Force Sensing and Artificial Neural Networks in Interactive Displays |
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