Patient-tailored classification for a NIRS triggered hand rehabilitation robot

Shunki Takemura, Joungseung Lee, Nobutaka Mukae, Kazuo Kiguchi, Koji Iihara, Makoto Hashizume, Jumpei Arata

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

Abstract

Robotic neurorehabilitation that provides the support movement for the affected limb triggered by brain signal has a great potential to improve the recovery for post-stroke patients. We are studying a hand rehabilitation robotic system that a robotic hand orthosis is moved triggered by Near-Infrared Spectroscopy. In this paper, we propose a new method to classify the motion intention out of the NIRS signal. The classification accuracy that is an essential factor to extract the users' motion intension, was significantly improved by parameterizing the individual hemodynamic response.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Cyborg and Bionic Systems, CBS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages632-636
Number of pages5
ISBN (Electronic)9781538673553
DOIs
Publication statusPublished - Jan 14 2019
Event2018 IEEE International Conference on Cyborg and Bionic Systems, CBS 2018 - Shenzhen, China
Duration: Oct 25 2018Oct 27 2018

Publication series

Name2018 IEEE International Conference on Cyborg and Bionic Systems, CBS 2018

Conference

Conference2018 IEEE International Conference on Cyborg and Bionic Systems, CBS 2018
CountryChina
CityShenzhen
Period10/25/1810/27/18

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Optimization

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  • Cite this

    Takemura, S., Lee, J., Mukae, N., Kiguchi, K., Iihara, K., Hashizume, M., & Arata, J. (2019). Patient-tailored classification for a NIRS triggered hand rehabilitation robot. In 2018 IEEE International Conference on Cyborg and Bionic Systems, CBS 2018 (pp. 632-636). [8612169] (2018 IEEE International Conference on Cyborg and Bionic Systems, CBS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CBS.2018.8612169