期刊
FRONTIERS IN NEUROROBOTICS
卷 14, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fnbot.2020.00048
关键词
brain-machine interface; frequency analysis; electroencephalography; empirical mode decomposition; exoskeleton; motor imagery
资金
- Spanish Ministry of Education and Professional Formation [CAS18/00048]
- Spanish Ministry of Science and Innovation
- Spanish State Agency of Research
- European Union through the European Regional Development Fund [RTI2018-096677-B-I00]
- Conselleria de Innovacion, Universidades, Ciencia y Sociedad Digital (Generalitat Valenciana)
- European Social Fund [GV/2019/009]
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.
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