A Force – Voltage Responsivity Stabilization Method for Piezoelectric Touch Panels in the Internet of Things

Abstract

Piezoelectric force touch panels are attractive as human-machine interfaces and 3-dimensional touch sensing in internet of things (IoT) applications. The piezoelectric material has the intrinsic ability to convert mechanical to electrical signals. But the force responsivity issue induced by different touch orientations can be unstable. This paper presents a piezoelectric touch panel that is sensitive to both capacitive and force stimulation. A touch orientation classification technique is developed to calibrate the detected force amplitude by training a machine learning model with finger induced capacitive information. A high and stable force voltage responsivity of 87.5% is achieved experimentally, demonstrating its potential significance in force touch based human-machine interactivity.