The invention discloses a
motor imagery electroencephalogram feature extraction method based on a matrix variable
Gaussian model. In the prior art, a
motor imagery electroencephalogram feature extraction method is insufficient in precision. The method comprises the following steps: 1, performing electroencephalogram test to establish a sample set; 2, performing
filter bank common space modal operation on the training sample set x; 3, constructing an inter-class weight matrix and an intra-class weight matrix; 4, calculating an intra-class space
covariance matrix and an intra-class frequency
covariance matrix; and 5, splitting the inter-class
scatter matrix. 6, establishing a projection matrix. 7, calculating a characteristic number pair; and 8, obtaining d-dimensional features for training.9, training an SVM model. And 10, detecting and identifying the
motor imagery of the detected person. The conventional
processing method ignores the spatial information in the electroencephalogram
signal. Matrix dimension reduction
processing is used, the thought of a matrix variable
Gaussian model is introduced, and the
utilization rate of space information is further increased.