TY - GEN
T1 - Assessment of motor imagery in gamma band using a lower limb exoskeleton
AU - Ortiz, M.
AU - Ianez, E.
AU - Gaxiola, J.
AU - Kilicarslan, A.
AU - Contreras-Vidal, J. L.
AU - Azorin, J. M.
N1 - Funding Information:
*Research was partially funded by Spanish ministry of Science, Innovation and Universities under the grant CAS18/00048 ‘José Castillejo’; by the project Walk - Controlling lower-limb exoskeletons by means of brain-machine interfaces to assist people with walking disabilities (RTI2018-096677-B-I00), funded by the Spanish Ministry of Science, Innovation and Universities, the Spanish State Agency of Research, and the European Union through the European Regional Development Fund; and by the Consellería de Innovación, Universidades, Ciencia y Sociedad Digital and the European Social fund in the framework of the project ‘Desarrollo de nuevas interfaces cerebro-máquina para la rehabilitación de miembro inferior’ (GV/2019/009).
Publisher Copyright:
© 2019 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/10
Y1 - 2019/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85076745326&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85076745326&partnerID=8YFLogxK
U2 - 10.1109/SMC.2019.8914483
DO - 10.1109/SMC.2019.8914483
M3 - Conference contribution
AN - SCOPUS:85076745326
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 2773
EP - 2778
BT - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
Y2 - 6 October 2019 through 9 October 2019
ER -