American Sign Language Recognition Using Sensory Glove and Neural Network

Abstract

a system was designed to recognize the Human hand manual alphabet of the American Sign Language utilizing artificial neural network that implement-ed to convert the (ASL) finger spilling alphabet into printed letters and using matlab to implement program that con-verting printed letters into animated (ASL) .the hardware system uses flex sensors these sensors were positioned on gloves to obtained The finger joint angle data when represent each letter of (ASL) and DAQ NI-6212 which was the interface between the sensors and the pc.DAQ produce 1000 readings per second the average of this read-ings is taken and normalization process is performed on the data and then applied to trained neural network to recognize which letter was performed by the hand and print it on the screen. On the other hand a matlab program was build using forward and inverse kinematics equations of human hand this program take normal language letters as input and produce an animated (ASL) letter as output. The hardware system have been trained and tested for (ASL) manual alphabet words and names recognition