Factors influencing low intension detection rate in a non-invasive EEG-based brain computer interface system
Motor imagery (MI) responses extracted from the brain in the form of EEG signals have been widely utilized for intention detection in brain computer interface (BCI) systems. However, due to the non-linearity and the non-stationarity of EEG signals, BCI systems suffer from low MI prediction rate with...
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Main Authors: | , , , |
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Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2020-10-01.
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A1234.567 |
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