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Assessing the Contribution of Covariance Information to the Electroencephalographic Signals of Brain–Computer Interfaces for Spinal Cord Injury Patients

Evaluación del aporte de la covarianza de las señales electroencefalográficas a las interfaces cerebro-computador de imaginación motora para pacientes con lesiones de médula espinal

dc.creatorFerrin Bolaños, Carlos
dc.creatorLoaiza-Correa, Humberto
dc.creatorPierre-Díaz, Jean
dc.creatorVélez-Ángel, Paulo
dc.date2019-09-20
dc.date.accessioned2021-03-18T21:12:30Z
dc.date.available2021-03-18T21:12:30Z
dc.identifierhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1392
dc.identifier10.22430/22565337.1392
dc.identifier.urihttp://test.repositoriodigital.com:8080/handle/123456789/11811
dc.descriptionNon-invasive EEG-based motor imagery brain–computer interfaces (miBCIs) promise to effectively restore the motor control of motor-impaired patients with conditions that include Spinal Cord Injury (SCI). Nonetheless, miBCIs should be further researched for this type of patients using low-cost EEG acquisition devices, such as the Emotiv EPOC, for home rehabilitation purposes. In this work, we describe in detail and compare ten miBCI architectures based on covariance information from EEG epochs. The latter were acquired with Emotiv EPOC from three control subjects and two SCI patients in order to decode the close and open hand intentions. Four out of the ten miBCIs use covariance information to create spatial filters; the rest employ covariance as a direct representation of the EEG signals, thus allowing the direct manipulation by Riemannian geometry. We found that, although all the interfaces present an overall accuracy above chance level, the miBCIs that use covariance as a direct representation of the EEG signals together with linear classifiers outperform miBCIs that use covariance for spatial filtering, both in control subjects and SCI. These results suggest the high potential of Riemannian geometry-based miBCIs for the rehabilitation of SCI patients with low-cost EEG acquisition devices.en-US
dc.descriptionLas interfaces cerebro-computadora no invasivas basadas en EEG de imaginación motora (miBCI) prometen restaurar efectivamente el control motor a pacientes con discapacidades motoras, por ejemplo, aquellos con lesión de la médula espinal (LME). Sin embargo, todavía es necesario investigar las miBCI, con fines de rehabilitación, para este tipo de pacientes que utilizan dispositivos de adquisición de señales EEG de bajo costo, tales como Emotiv EPOC. En este trabajo, se describe en detalle y se comparan diez arquitecturas miBCI basadas en información de covarianza de señales EEG, adquiridas con Emotiv EPOC, para la decodificación de intención de mano abierta y cerrada en tres sujetos control y dos pacientes con LME cervical. Cuatro de estas diez miBCI usan información de covarianza para construir filtros espaciales y el resto usa la información covarianza como una representación directa de las señales EEG, permitiendo la manipulación directa mediante geometría de Riemann. Como resultado, se encontró que, a pesar de que todas las arquitecturas miBCI tienen una precisión general por encima del nivel de azar, las que utilizan la covarianza como representación directa de las señales EEG junto con clasificadores lineales, superan las miBCI que usan la covarianza para el filtrado espacial, tanto en sujetos de control como en pacientes con LME. Estos resultados sugieren un alto potencial de las miBCI basadas en la geometría de Riemann para la rehabilitación de pacientes con LME, utilizando dispositivos de adquisición de EEG de bajo costo.  es-ES
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dc.publisherInstituto Tecnológico Metropolitano (ITM)en-US
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1392/1368
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1392/1451
dc.relationhttps://revistas.itm.edu.co/index.php/tecnologicas/article/view/1392/1480
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dc.rightsCopyright (c) 2019 TecnoLógicasen-US
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0en-US
dc.sourceTecnoLógicas; Vol. 22 No. 46 (2019); 213-231en-US
dc.sourceTecnoLógicas; Vol. 22 Núm. 46 (2019); 213-231es-ES
dc.source2256-5337
dc.source0123-7799
dc.subjectBrain-computer interfaceen-US
dc.subjectMotor imageryen-US
dc.subjectInformation geometryen-US
dc.subjectSpatial filtersen-US
dc.subjectSpinal cord injuryen-US
dc.subjectInterfaces cerebro-computadores-ES
dc.subjectImaginación motoraes-ES
dc.subjectGeometría de Riemannes-ES
dc.subjectgeometría de la informaciónes-ES
dc.subjectfiltrado espaciales-ES
dc.subjectlesión de médula espinales-ES
dc.titleAssessing the Contribution of Covariance Information to the Electroencephalographic Signals of Brain–Computer Interfaces for Spinal Cord Injury Patientsen-US
dc.titleEvaluación del aporte de la covarianza de las señales electroencefalográficas a las interfaces cerebro-computador de imaginación motora para pacientes con lesiones de médula espinales-ES
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typeResearch Papersen-US
dc.typeArtículos de investigaciónes-ES


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