The invention discloses a sign
language translation method based on a BP neural network. The sign
language translation method is characterized by comprising the following steps: 1, acquiring a gesturevoltage
signal by utilizing
Raspberry Pi 3B through a wearable data glove; 2, compiling sign language words and common sign language sentences corresponding to each group of gesture
voltage signals into a sign language
sentence library by utilizing a
signal screening program; 3, writing a
neural network classification program comprising a BP neural
network structure framework model, a
data transmission module and a storage module, wherein the BP neural
network structure framework model adopts a three-layer neural network comprising an input layer, an output layer and a
hidden layer; 4, converting the gesture
voltage signals received each time into sign language words through a BP neural network framework model; and 5, converting the sign language words obtained in the step 4 into sign language word groups within a period of time, matching the sign language word groups with a sign language statement
library, associating and filling into sentences, and outputting a result. According tothe invention, automatic real-time translation identification of sign language is realized by combining a neural network and a sensing technology.