Active acoustic sensing for determining touch location on an elastic surface

In this paper, we describe the development and testing of an active acoustic sensing (AAS) touch interface. The interface detects subtle changes in the vibrational characteristics of an elastic panel when a user applies a small force to the surface at different locations. The system consists of a panel with an affixed force exciter and vibration sensor to monitor the panel vibrations. An automated system was used to manipulate a stylus to apply a light force to the panel at an array of known locations and the vibrational response of the panel was recorded by the affixed sensor. We employed a rectangular grid of 414 points with 10mm spacing on a 2mm thick acrylic panel of dimensions 18cm by 23cm. Features of the recordings were employed as training data for a deep neural network. The results demonstrate the viability of the AAS interface, and they show the relative performance of the system as a function of the selected features. The demonstration platform achieved a classification accuracy of 100% and a mean distance error of 0.20mm for regression. The best-performing feature sets were those that contained sufficient spectral resolution to discriminate subtle changes in the center frequencies and amplitudes of the panel’s modal resonances in response to small changes in touch location. The AAS touch interface is a practical and inexpensive means to provide accurate touch sensing for large surfaces, such as displays, televisions, and information kiosks. •Prototype vibration-based touch sensor presented.•Employed machine learning techniques informed by analysis of physical system.•Achieved 100 % classification accuracy at 10mm resolution.