Abstract:With the wide application of computers and the development of wearable electronic devices, the combination of humancomputer interaction and wearable devices has become a research hotspot. Gesture recognition technology plays an important role in the field of humancomputer interaction. An intelligent gesture recognition method is proposes based on electrical measurement. The sensor device is used to collect the wrist boundary voltage data. At the same time, the deep voltage neural network is used to classify the collected voltage data, and finally the purpose of gesture recognition is realized. The experiment verifies the feasibility of classifying gestures by electrical measurement data. After adding deep neural network to the gesture recognition system, the correct recognition rate of gestures is over 90%, which proves that the system has better portability, stability and realtime. Sexuality provides new ideas for the design of intelligent gesture recognition systems.