A Framework for Analyzing Both Finger-Surface and Tool-Surface Interactions

2020

Miscellaneous

hi

We interact with surfaces both through our fingers and by means of tools every day. In this process, our tactile mechanoreceptors transduce rich contact-elicited signals to neuronal events, enabling ubiquitous tasks such as object recognition and surface-feature discrimination. Past research has shed light on the neural mechanisms of surface perception, but the involved interaction complexity tends to obfuscate the origin of the produced contact signals for all but the simplest interactions. The manner in which soft versus hard contact partners (skin versus tool) shape the dynamical signals is particularly elusive. To address this gap in our understanding about the mechanical basis of surface encoding, we designed a novel experimental apparatus that uses optical motion capture, miniature high-bandwidth accelerometers, and a six-axis force/torque sensor to capture relevant details of the contact interaction. We measured contact signals for finger and tool interactions with a set of diverse hard textures and analyzed the data with advanced signal-processing, stochastic time-series, and nonlinear time-series techniques. Our approach provides insights into several salient phenomena of finger- and tool-surface interaction. For example, segments of the signals relate to geometrical and mechanical properties of the contact pair. The results may not only elucidate our understanding of human skin as a complex soft matter, but they may also help in the design of prosthetics, electronic skin, human-machine interfaces and surgical robots.

@misc{Khojasteh20-EHWIP-Surface,
  title = {A Framework for Analyzing Both Finger-Surface and Tool-Surface Interactions},
  author = {Khojasteh, Behnam and Kuchenbecker, Katherine J.},
  howpublished = {Work-in-progress poster presented at EuroHaptics},
  address = {Leiden, The Netherlands},
  month = sep,
  year = {2020},
  doi = {},
  month_numeric = {9}
}