Assessment of motor imagery in gamma band using a lower limb exoskeleton

M. Ortiz, E. Ianez, J. Gaxiola, A. Kilicarslan, J. L. Contreras-Vidal, J. M. Azorin

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

2 Scopus citations

Abstract

The use of a brain-machine interface (BMI) in combination with powered exoskeletons can assist patients with lower limb disabilities to walk again. These neurorobotic systems are commonly based on motor imagery, but their performance may suffer from lack of user engagement in the task or from cognitive load due to multi-tasking. The present paper shows a novel algorithm based on the gamma spectral band, using the Stockwell transform and a set of smoothing filters, to assess the quality of and improve the decoding of motor imagery during the use of a BMI-Rex exoskeleton system. The results computed in a pseudo-online scenario reveal a high accuracy with a very low false positive ratio.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2773-2778
Number of pages6
ISBN (Electronic)9781728145693
DOIs
StatePublished - Oct 2019
Event2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 - Bari, Italy
Duration: Oct 6 2019Oct 9 2019

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2019-October
ISSN (Print)1062-922X

Other

Other2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
CountryItaly
CityBari
Period10/6/1910/9/19

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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