Sensory Perception & Interaction, Research Group

The bulk of applications for haptic feedback employ direct rendering
approaches wherein a user touches a virtual model of some “real” thing, often
displayed graphically as well. We propose a new class of applications based on
abstract messages, ranging from “haptic icons” – brief signals conveying an object’s
or event’s state, function or content – to an expressive haptic language for
interpersonal communication. Building this language requires us to understand
how synthetic haptic signals are perceived, and what they can mean to us.
Experiments presented here address the perception question by using an efficient
version of Multidimensional Scaling (MDS) to extract perceptual axes for
complex haptic icons: once this space is mapped, icons can be designed to
maximize both differentiability and individual salience. Results show that a set
of icons constructed by varying the frequency, magnitude and shape of 2-sec,
time-invariant wave shapes map to two perceptual axes, which differ depending
on the signals’ frequency range; and suggest that expressive capability is maximized
in one frequency subspace.