Motor imagery EEG detection by empirical mode decomposition

The paper investigates the possibility of using empirical mode decomposition (EMD) method to detect the mu rhythm of motor imagery EEG signal. Recently the mu rhythm by motor imagination has been used as a reliable EEG pattern for brain-computer interface (BCI) system. Considering the non-stationary characteristics of the motor imagery EEG, the EMD method is proposed to detect the mu rhythm during left and right hand movement imagination. By analyzing the instantaneous amplitude and instantaneous frequency of the intrinsic mode functions (IMFs), the mu rhythm can be detected. And by Hilbert marginal spectrum, the ERD/ERS phenomenon of mu rhythm can be found. The results in this paper demonstrate that the EMD method is a effective time-frequency analysis tool for non-stationary EEG signal.