Towards a numerically tractable model for the auditory substitution of tactile percepts

We refer to channels of communication that link the user to information systems as cognitive communication channels. One especially interesting research topic related to cognitive communication channels deals with a special application called sensory substitution, when information is conveyed through a channel other than the one that is normally used for the given application. Our goal is to develop engineering systems for the remote teleoperation of robots using sensory substitution to convey feedback information in meaningful ways. Such applications could help reduce the cognitive load for the user on the one hand, and help alleviate the effect of control instabilities and hidden parameters on the other. A large part of our research deals with how to provide information on tactile percepts - otherwise inaccessible to the remote user - through sound. In this paper, we present one possible mapping between tactile percepts and auditory parameters. Through a set of controlled experiments, we show that the parameters used are meaningful and the sounds can at some level be learned by users as a substitute for tactile perception. Analyzing the error statistics of the experiments, we argue that it would be worthwhile to create a system in which the sound parameters could be locally tuned to enhance performance on a user-per-user basis. To this end, we convert the analytical descriptions of our sounds into an higher-order singular value decomposition (HOSVD) based tensor product model form. In order to be able to apply a wide range of mathematical analysis tools - such as principal component analysis and user performance-oriented adaptivity - we demonstrate that it is possible to convert our models into such canonical forms.