An Interactive Tool for Simulating Mid-Air Ultrasound Tactons on the Skin

TL;DR

The paper addresses the challenge of predicting how five temporal parameters ($A$, $f_{AM}$, $f_e$, $w_{AM1}$, $t_d$) and three spatiotemporal parameters (shape, $d$, $v$) govern mid-air ultrasound Tactons by introducing a Python-based interactive simulation that computes the skin vibration response at any point via $p(t)$ for a single focal point. It presents a computational model where the intensity at a skin point depends on distance through $S(D(\vec{x}(t),\vec{a}))$, with the final signal $p(\vec{x}(t),\vec{a},t)$ derived from the carrier $U(t)$ and temporal envelopes, visualizing both waveform and spectrum. Preliminary measurements using a STRATOS Explore device and a laser vibrometer for 15 Tactons across AM, STM, and AM+STM show that the simulation captures key spectral characteristics, such as harmonics at multiples of $f_{AM}$ and $f_d$, and the peak alignment with the input AM frequency, validating the tool's potential for design guidance despite limitations of the paper-skin measurement setup. Overall, the interactive tool offers a practical means for rapid prototyping and informed parameter exploration in mid-air ultrasound haptics, with future work planned to broaden parameters, relax modeling assumptions, and open-source the implementation.

Abstract

Mid-air ultrasound haptic technology offers a myriad of temporal and spatial parameters for contactless haptic design. Yet, predicting how these parameters interact to render an ultrasound signal is difficult before testing them on a mid-air ultrasound haptic device. Thus, haptic designers often use a trial-and-error process with different parameter combinations to obtain desired tactile patterns (i.e., Tactons) for user applications. We propose an interactive tool with five temporal and three spatiotemporal design parameters that can simulate the temporal and spectral properties of stimulation at specific skin points. As a preliminary verification, we measured vibrations induced from the ultrasound Tactons varying on one temporal and two spatiotemporal parameters. The measurements and simulation showed similar results for three different ultrasound rendering techniques, suggesting the efficacy of the simulation tool. We present key insights from the simulation and discuss future directions for enhancing the capabilities of simulations.

Figures (3)

• Figure 1: Plots for the intensity of stimulation by a single focal point at the height h and the interactive simulation tool: (a) The intensity of stimulation decreases with distance from the focal point carter2013ultrahaptics. (b) The relative intensity determined by the distance between a focal point and the mid-air ultrasound device. (c) The control panel in our interactive tool for manipulating parameters in temporal and spatiotemporal configurations. The dropdowns allow users to select design parameters and a position ($\vec{a} = (a,~b)$) on the skin. (d) The visualization panel showing the 2D stimulated skin area (Left) and vibration waveform (Right) at a specific point on the skin. The sky-colored line represents the trajectory of a focal point, the black dotted line represents the borderline influenced by the stimulation, and the "X" symbol represents the point selected to see the effects of the stimulation by the Tacton. The three plots (Right) display the temporal plot of the Tacton, and the temporal and spectral plots of the stimulation at the selected point $\vec{a}$ by the user .
• Figure 2: Our measurement setup. (a) We used a laser vibrometer to measure vibrations on paper induced by mid-air ultrasound Tactons. (b) In all measurements, we measured the vibrations at the same 5 points, spaced at 5 mm intervals.
• Figure 3: Three exemplar comparisons for pure AM rendering, pure STM rendering, and combination of AM and STM rendering, between simulations (blue) and measurements (red).