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In this paper, the differences between two motor imagery tasks are captured through microstate parameters (occurrence, duration and coverage, and mean spatial correlation (Mspatcorr)) derived from a novel method based on electroencephalogram microstate and Teager energy operator. The results show that the significance between microstate parameters for two tasks is different ( P &lt; 0.05) with paired t -test. Furthermore, these microstate parameters are utilized as features. Support vector machine is utilized to classify the two tasks with a mean accuracy of 93.93%, which yielded superior performance compared to the other methods.

Exploring differences for motor imagery using Teager energy operator-based EEG microstate analyses