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Evolving BCI Therapy - Engaging Brain State Dynamics
Motor imagery brain-computer interface (BCI) by using of deep-learning models is proposed in this paper. In which, we used the electroencephalogram (EEG) signals of motor imagery (MI-EEG) to identify different imagery activities. The brain dynamics of motor imagery are usually measured by EEG as non-stationary time series of low signal-to-noise ratio. However, a variety of methods have been previously developed to classify MI-EEG signals getting not satisfactory results owing to lack ofdoi:10.5772/intechopen.75009 fatcat:djadkjgq3ff2vmo7uxzbemoimm