An EEG database for the cognitive assessment of motor imagery during walking with a lower-limb exoskeleton

One important point in the development of a brain-machine Interface (BMI) commanding an exoskeleton is the assessment of the cognitive engagement of the subject during the motor imagery tasks conducted. However, there are not many databases that provide electroencephalography (EEG) data during the u...

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Bibliographic Details
Authors: Ortiz, Mario, de la Ossa, Luis, Juan Poveda, Javier V., Iáñez, Eduardo, Torricelli, Diego, Tornero, Jesús, Azorín, José M.
Format: article
Publication Date:2023
Country:España
Institution:Universidad Miguel Hernández de Elche
Repository:REDIUMH. Depósito Digital de la UMH
OAI Identifier:oai:dnet:rediumh_____::2eb00e4b9d85691f9d26094e114096ca
Online Access:https://hdl.handle.net/11000/39682
Access Level:Open access
Keyword:Brain-Machine Interface (BMI)
Electroencephalography (EEG)
motor imagery
lower-limb exoskeleton
attention to gait
CDU::6 - Ciencias aplicadas::62 - Ingeniería. Tecnología
CDU::6 - Ciencias aplicadas::61 - Medicina::612 - Fisiología
CDU::0 - Generalidades.::04 - Ciencia y tecnología de los ordenadores. Informática.
Description
Summary:One important point in the development of a brain-machine Interface (BMI) commanding an exoskeleton is the assessment of the cognitive engagement of the subject during the motor imagery tasks conducted. However, there are not many databases that provide electroencephalography (EEG) data during the use of a lower-limb exoskeleton. The current paper presents a database designed with an experimental protocol aiming to assess not only motor imagery during the control of the device, but also the attention to gait on flat and inclined surfaces. The research was conducted as an EUROBENCH subproject in the facilities sited in Hospital Los Madroños, Brunete (Madrid). The data validation reaches accuracies over 70% in the assessment of motor imagery and attention to gait, which marks the present database as a valuable resource for researches interested on developing and testing new EEG-based BMIs.

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