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However, several traditional BCI recognition algorithms have the \u201cone person, one model\u201d issue, where the convergence of the recognition model\u2019s training process is complicated. In this study, a new BCI model with a Dense long short\u2010term memory (Dense\u2010LSTM) algorithm is proposed, which combines the event\u2010related desynchronization (ERD) and the event\u2010related synchronization (ERS) of the imagery\u2010based BCI; model training and testing were conducted with its own data set. Furthermore, a new experimental platform was built to decode the neural activity of different subjects in a static state. 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