Abstract
High detection accuracy in piezoelectric-based force sensing in interactive displays has gained global attention. To achieve this, artificial neural networks (ANN)—successful and widely used machine learning algorithms—have been demonstrated to be potentially powerful tools, providing acceptable location detection accuracy of 95.2% and force level recognition of 93.3% in a previous study. While these values might be acceptable for conventional operations, e.g., opening a folder, they must be boosted for applications where intensive operations are performed. Furthermore, the relatively high computational cost reported prevents the popularity of ANN-based techniques in conventional artificial intelligence (AI) chip-free end-terminals. In this article, an ANN is designed and optimized for piezoelectric-based touch panels in interactive displays for the first time. The presented technique experimentally allows a conventional smart device to work smoothly with a high detection accuracy of above 97% for both location and force level detection with a low computational cost, thereby advancing the user experience, and serviced by piezoelectric-based touch interfaces in displays.
Highlights
Touch-based interactivity has become a must-have function in smartphones and has created abundant applications in the last decade, improving users human-machine interactivity (HMI) in a convenient and highly efficient manner
Since no research has yet been reported about the optimization of an artificial neural networks (ANN) for piezoelectric-based force touch panels, in this paper, we investigate the relationship between the ANN hyperparameters and the detection accuracy in terms of location and force level interpretation
We study the effects of ANN structures on the computational cost, which is directly related to the processing time and power consumption of smart electronic devices and systems
Summary
Touch-based interactivity has become a must-have function in smartphones and has created abundant applications in the last decade, improving users human-machine interactivity (HMI) in a convenient and highly efficient manner. The rapid development of information technology requires more data to be exchanged between the user and the end-terminal nowadays, boosting the popularity of three-dimensional force touch sensing. 6S) and piezoresistive (e.g., iPhone X) techniques The former integrates a layer of capacitive sensors into the backlight of the display to measure the distance shift due to the applied force between the cover glass and the backlight. The latter utilizes the force-induced resistance change at the inserted electrodes to interpret the force level. To obtain the force sensing functionality without affecting the capacitive touch sensing, both the capacitive and the piezoresistive techniques require
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