The invention discloses a method and device for identifying a somatosensory evoked potential component based on a support vector machine, comprising an acquisition building unit for acquiring median nerve somatosensory evoked potentials of known origin. The time-frequency components of median nerve somatosensory evoked potentials (MNEPs) are obtained by time-frequency conversion. The time-frequency components of MNEPs were matrices transformed to obtain the time-frequency component eigenvectors. The time-frequency component eigenvectors were used as inputs to construct a multi-stage support vector classifier (SVC). The identification unit is used for classifying and identifying the time-frequency components of the median nerve somatosensory evoked potential to be identified according to the multistage support vector classifier, and determining the source corresponding to the time-frequency components of the median nerve somatosensory evoked potential to be identified, so that a multi-stage support vector classifier is designed to improve the sensitivity and specificity of time-frequency classification of somatosensory evoked potentials and effectively overcome the problem of smallsample size.
Method and device for identifying somatosensory evoked potential components based on support vector machine