The invention discloses a gesture recognition method fusing an electromyographic signal and a visual image, which comprises the following steps: acquiring an electromyographic signal by using a high-density electromyographic signal acquisition arm band, acquiring a visual image by using a camera, and fusing an electromyographic image converted from the electromyographic signal and the visual image into one image; and inputting an image fused by the surface myoelectricity image and the visual image into an image classification module for identification and classification. According to the method, the surface electromyogram signals and the visual images do not need to be identified and classified by using two different network structures, only the surface electromyogram signals and the visual images need to be transmitted into a network architecture at the same time, identification and classification can be carried out by using the same network, the network complexity can be effectively reduced, and limited resources are saved. According to the method, the form that gesture recognition is carried out by using a single input mode in each set of traditional networks can be improved, and the respective limitations that the surface electromyogram signals and the visual images are respectively used for gesture recognition are improved.
Gesture recognition method fusing electromyographic signals and visual image