The invention discloses a method for classifying sensory substances based on olfactory brain waves and GS-SVM, which comprises the following steps of: S1, utilizing brain-computer interface system, i.e., the brain electric instrument, to acquire the electroencephalogram spectrum information of the subject; S2, preprocessing the acquired EEG spectrum data; S3, performing feature extraction on thepreprocessed atlas data based on the linear characteristic and the nonlinear characteristic analysis, 76-dimensional data including peak, mean, standard deviation, center value, center frequency, power sum and LZC complexity of alpha, beta, theta frequency bands are used as brain electrical characteristics in the study of brain electrical signals; S4, adopting a network format search support vector machine (GS-SVM) for pattern recognition. According to the method for classifying sensory substances based on olfactory brain waves and GS-SVM, the physiological morphology of the human brain information processing process in the product evaluation process is truly restored, which has extremely important significance in the fields of clinical medicine and cognitive science and can be widely usedin the sensory evaluation of substances, making the sensory evaluation process more concise, more standardized, precise and scientific.