Sign language communication and authentication using sensor fusion of hand glove and photometric signals

This paper proposes a sign language interpretation system by a combination of data glove and photoplethysmograph sensor measurements collected concurrently from data glove and PPG devices. This system is tested on many numbers of trials by different subjects performing a set of particular shapes using the American Sign Language (ASL). The sign language being the natural way of communication for the hearing and speech impaired people, there are systems being developed to understand the sign language and to produce communication. As an enhancement to the communication system for the targeted audience, authentication systems that can understand sign language would be of a great help. The focus of this paper is on the avoidance of skilled forgers try to seek the genuine sign language symbols in many numbers of trials. The reinforcement of sign language signals by the Photoplethesomograph signals were found to be increasing the gap in the Euclidian distances between forgers and the genuine template feature, thus prohibiting them from thrive forging. It has been clearly proved by our repetitive experiments here, on various subjects using the combinational features. The cause of benefits in the proposed system in eliminating forge attempts is due to the biometric differences found in data glove signal characteristics and level of bilateral hand dimensional dissimilarities plus arterial blood pulsation of individuals. Furthermore, we found some predominant sensors essential in this authentication process and trying to eliminate un useful sensors which are of less importance in hand glove thus making the optimization of hardware.