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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Ortiz, Mario | - |
dc.contributor.author | Iáñez, Eduardo | - |
dc.contributor.author | Contreras Vidal, José Luis | - |
dc.contributor.author | Azorín Poveda, José María | - |
dc.contributor.other | Departamentos de la UMH::Ingeniería de Sistemas y Automática | es |
dc.date.accessioned | 2020-10-15T07:38:25Z | - |
dc.date.available | 2020-10-15T07:38:25Z | - |
dc.date.created | 2020-06-18 | - |
dc.date.issued | 2020-10-15 | - |
dc.identifier.issn | 1662-5218 | - |
dc.identifier.uri | http://hdl.handle.net/11000/6503 | - |
dc.description.abstract | The use of brain-machine interfaces in combination with robotic exoskeletons is usually based on the analysis of the changes in power that some brain rhythms experience during a motion event. However, this variation in power is frequently obtained through frequency filtering and power estimation using the Fourier analysis. This paper explores the decomposition of the brain rhythms based on the Empirical Mode Decomposition, as an alternative for the analysis of electroencephalographic (EEG) signals, due to its adaptive capability to the local oscillations of the data, showcasing it as a viable tool for future BMI algorithms based on motor related events. | es |
dc.description.sponsorship | by the Spanish Ministry of Science and Innovation, the Spanish State Agency of Research, and the European Union through the European Regional Development Fund in the framework of the project Walk—Controlling lower-limb exoskeletons by means of brain-machine interfaces to assist people with walking disabilities (RTI2018-096677-B-I00); | - |
dc.description.sponsorship | and by the Consellería de Innovación, Universidades, Ciencia y Sociedad Digital (Generalitat Valenciana) 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 | - |
dc.description.sponsorship | Authors would like to thank specially Kevin Nathan and the rest of the laboratory of JC-V for their help during the experimental trials and Atilla Kilicarslan for his help with the implementation of H∞ algorithm. | - |
dc.format | application/pdf | es |
dc.format.extent | 13 | es |
dc.language.iso | eng | es |
dc.rights | info:eu-repo/semantics/openAccess | es |
dc.subject | brain-machine interface | es |
dc.subject | frequency analysis | es |
dc.subject | electroencephalography | es |
dc.subject | empirical mode decomposition | es |
dc.subject | exoskeleton, motor imagery | es |
dc.subject.other | 62 - Ingeniería. Tecnología | es |
dc.title | Analysis of the EEG Rhythms Based on the Empirical Mode Decomposition During Motor Imagery When Using a Lower-Limb Exoskeleton. A Case Study | es |
dc.type | info:eu-repo/semantics/article | es |
dc.identifier.doi | 10.3389/fnbot.2020.00048 | - |
dc.relation.publisherversion | http://dx.doi.org/ 10.3389/fnbot.2020.00048 | - |
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