Please use this identifier to cite or link to this item: https://hdl.handle.net/11000/6503

Analysis of the EEG Rhythms Based on the Empirical Mode Decomposition During Motor Imagery When Using a Lower-Limb Exoskeleton. A Case Study


Thumbnail

View/Open:
 7-fnbot-14-00048.pdf
2,29 MB
Adobe PDF
Share:
Title:
Analysis of the EEG Rhythms Based on the Empirical Mode Decomposition During Motor Imagery When Using a Lower-Limb Exoskeleton. A Case Study
Authors:
Ortiz García, Mario
Iáñez Martínez, Eduardo
Contreras Vidal, José Luis
Azorín Poveda, José María
Department:
Departamentos de la UMH::Ingeniería de Sistemas y Automática
Issue Date:
2020-06-18
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.
Keywords/Subjects:
brain-machine interface
frequency analysis
electroencephalography
empirical mode decomposition
exoskeleton, motor imagery
Type of document:
application/pdf
Access rights:
info:eu-repo/semantics/openAccess
Appears in Collections:
Artículos



Creative Commons ???jsp.display-item.text9???