Tactile Sensing, Information, and Feedback via Wave Propagation

A longstanding goal of engineering has been to realize haptic interfaces that can convey realistic sensations of touch, comparable to signals presented via visual or audio displays. Today, this ideal remains far from realization, due to the difficulty of characterizing and electronically reproducing the complex and dynamic tactile signals that are produced during even the simplest touch interactions. The overarching goal of the proposed PhD research is to capture whole-hand tactile signals produced during natural interactions, to characterize the information content in these signals, and to use the results to guide the design of new electronic devices for tactile feedback.The first part of the thesis is motivated by recent findings that touch contact elicits tactile signals can travel long distances in the hand. In order to elucidate the role of these processes in natural touch interactions, I first developed wearable sensing instrumentation, comprised of high channel count accelerometer arrays, for capturing whole-hand mechanical signals during manual interactions. The temporal, spatial and frequency structure of the signals on the hand were found to vary systematically with hand interactions and could be used to identify them. These results are consistent with findings in perception research indicating that vibrotactile signals distributed throughout the hand can transmit information regarding explored and manipulated objects.In the second part of the thesis, I investigated the information content in these tactile waves using signal processing methods. Motivated by the structure in these signals, and neuroscience considerations, I sought to extract informative representations of these signals based on solutions of an optimization problem formulated as convolutional sparse coding of natural tactile signals. This yielded a dictionary of spatiotemporal primitives that provided compact descriptions of information in high dimensional tactile signals in the whole hand, sufficient to accurately classify touched objects and interactions. The primitive patterns were organized in ways reflecting the anatomy and function of the hand and the manual activities involved. In the final part of the PhD, informed by the findings from parts 1 and 2 about spatiotemporal distributions of touch-elicited tactile signals, I developed new methods for distributed haptic feedback adapted to the mechanics and dynamics of the skin. I developed new spatiotemporal haptic effects by using a single actuator to generate tactile stimuli with dynamically controlled spatial extent, based on the frequency-dependent damping of propagating waves in the skin. I designed a wearable haptic feedback device based on compliant liquid dielectric actuators, which can render tactile feedback with substantial displacements and forces via a large active area interfacing the skin. This yielded practical haptic technologies that can produce rich touch feedback for human-computer interaction or virtual reality