Dynamic Texture Decoding Using a Neuromorphic Multilayer Tactile Sensor

Harrison Nguyen, Luke Osborn, Mark Iskarous, Christopher Shallal, Christopher Hunt, Joseph Betthauser, Nitish Thakor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Prosthetic limbs would benefit from tactile feedback to provide sensory information when interacting with the environment, such as adjusting grasps using force feedback or palpating texture. In this work, we demonstrate how a multilayer tactile sensor can be used for palpation, and enhance the ability to discriminate between touch interfaces. Inspired by mechanoreceptors in skin, the multilayer sensor consists of multiple textile force sensing elements. The novelty of this work lies in the application of a multilayer sensor, one that produces touch receptor like (neuromorphic) output, to texture classification by using a classifier based on sparse recovery. This approach is shown to be capable of palpation, achieving classification accuracies as high as 97% on a distinct texture set. Using compressed sensing and sparse recovery, the multilayer sensor can decode texture under dynamic conditions, potentially providing amputees the ability to perceive rich haptic information while using their prosthesis.

Original languageEnglish (US)
Title of host publication2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538636039
DOIs
StatePublished - Dec 20 2018
Event2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018 - Cleveland, United States
Duration: Oct 17 2018Oct 19 2018

Publication series

Name2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018 - Proceedings

Other

Other2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018
CountryUnited States
CityCleveland
Period10/17/1810/19/18

Keywords

  • Compressed Sensing Sparse Recovery
  • Haptics
  • Neuromorphic Model
  • Supervised Learning
  • Tactile Sensor

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Health Informatics
  • Instrumentation
  • Signal Processing
  • Biomedical Engineering

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