A real-time portable sign language translation system

In this paper, a wireless hand gesture recognition glove is proposed for real-time translation of Taiwanese sign language. To discriminate between different hand gestures, we have flex and inertial sensors embedded into the glove so that the three most important parameters, i.e., the posture of fingers, orientation of the palm, and motion of the hand, defined in Taiwanese Sign Language can be recognized without ambiguity. The finger flexion postures acquired by flex sensors, the palm orientation acquired by G-sensor, and the motion trajectory acquired by gyroscope are used as the input signals of the proposed system. The input signals will be acquired and examined periodically to see if it is a legal sign language gesture or not. Once the sampled signal can last longer than a predefined clock cycles, it is regarded as a valid gesture and will be sent to cell phone via Bluetooth for gesture discrimination and speech translation. With the proposed architecture and algorithm, the accuracy for gesture recognition is quite satisfactory. As we can see in experiments that an accuracy rate up to 94% on sensitivity for gesture recognition can be achieved which justifies the superiority of the proposed architecture.