Spike and slow wave complex detection and identification method and system based on feature fusion

The invention provides a spike and slow wave complex detection and identification method based on feature fusion. The spike and slow wave complex detection and identification method comprises the following steps of 1, extracting time-frequency domain features according to labeled sample data of a spike and slow wave complex database and a normal brain wave database; estimating distance features by utilizing the spike and slow wave complex database, the normal brain wave database and a spike and slow wave complex template library, establishing a spike and slow wave complex feature library and a normal waveform feature library through the features, and further training a classification model; step 2, estimating the distance degree between the effective unknown type brain wave data and the spike and slow wave complex template data by using a DTW algorithm; and step 3, extracting time-frequency domain features of the unknown type brain wave data, fusing the time-frequency domain features and the distance degree f