Parallel convolutional neural network and empirical mode decomposition for high accuracy in motor imagery EEG signal classification
In recent years, the utilization of motor imagery (MI) signals derived from electroencephalography (EEG) has shown promising applications in controlling various devices such as wheelchairs, assistive technologies, and driverless vehicles. However, decoding EEG signals poses significant challenges du...
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Published in | PloS one Vol. 20; no. 1; p. e0311942 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Public Library of Science (PLoS)
01.01.2025
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Online Access | Get full text |
ISSN | 1932-6203 |
DOI | 10.1371/journal.pone.0311942 |
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