Live Demonstration: Augmented Reality Prosthesis Training with Real- Time Hand Trajectory Prediction and Neuromorphic Tactile Encoding

Christopher L. Hunt, Avinash Sharma, Mark M. Iskarous, Nitish V Thakor

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

Abstract

This demonstration is a combination of the work described in [1], [2], and [3]. The goal of this work is to improve the efficacy of upper-limb prosthesis training protocols using visual feedback based on tactile and proprioceptive sensorization in an augmented reality environment.

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

Other

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

ASJC Scopus subject areas

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

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  • Cite this

    Hunt, C. L., Sharma, A., Iskarous, M. M., & Thakor, N. V. (2018). Live Demonstration: Augmented Reality Prosthesis Training with Real- Time Hand Trajectory Prediction and Neuromorphic Tactile Encoding. In 2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018 - Proceedings [8584670] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIOCAS.2018.8584670