Optimal hand sign selection using information theory for custom sign-based communication

Improving the communication abilities of people suffering from speech disorders or hearing impairments and who are struggling to learn sign or spoken language can improve their quality of life. However, methods to assist such people are not varied, and those that consider the degree of physical disability usually fail to attend particular needs. Thus, it is necessary to provide various communication methods according to the characteristics of each physical disability. In this paper, we devise a customized hand sign recognition system according to the degree of physical disability, and propose a method to select a customized set of signs comprising specific hand motions that an individual can effortlessly perform. We consider the optimal set as that providing high reliability and efficiency to realize smooth communication and apply information theory towards their selection. That is, we consider hand sign recognition from myoelectric potentials elicited by finger movement as a communication channel. Then, the optimal hand sign set is determined considering the set with the maximum channel capacity, as it reflects the most reliable and efficient combination. Finally, experimental results obtained from three subjects verify that the proposed method can determine the optimal set of hand signs according to each subject and that increasing the available hand signs or choosing hand signs with high recognition rate do not necessarily contribute to the optimal set.