Research progress of electroencephalogram (EEG) classification method and its application based on support vector machine (SVM)

This article introduces the classification method of support vector machine (SVM) on electroencephalogram (EEG) and its advantages and disadvantages. At the same time, it studies the improvement of its classification ability by using different optimization methods, and then focuses on specific application areas. For example, epilepsy, mental classification, exercise status judgment, etc. compare and analyze the optimization capabilities of different methods, and finally propose the development and prospects of support vector machines in EEG signal classification.