Silent speech recognition method based on face and neck surface myoelectricity

The invention discloses a silent speech recognition method based on face and neck surface electromyography, and the method comprises the steps: carrying out the data preprocessing and feature extraction of surface electromyography signals collected by a high-density electrode array and discrete electrodes, obtaining a high-density sEMG image set and a channel sparse sEMG image set, and constructing a source domain database and a target domain database; then training the word classification deep neural network by using the source domain database, and completing the calibration of the network in the target domain database by using transfer learning; and if the test user expresses the words silently under the input of the discrete electrodes, wherein the calibrated network can complete word classification and realize silent speech recognition. According to the invention, the capability of capturing abundant muscle activation mode information of a high-density electrode array and the portability and easiness in w