Static Finger Language Recognition for Handicapped Aphasiacs

This paper describes a finger language recognition system for handicapped aphasiacs, who are able to express their intents only by using ´finger language´. Finger language is different from sign language in the sense that it is composed of simple hand gestures, each representing a predefined meaning. The system consists of a low-cost fiber data glove, a small-scale finger language recognition subsystem, and a commercial text-to-speech (TTS) subsystem. The data glove receives the optical fiber signals associated with a given hand gesture, and the recognition subsystem translates the intended meaning of the given hand gesture. The recognized meaning is fed to the TTS subsystem, which converts it to vocal signals. Our experiment shows the system can achieve 99.97% accuracy rate.