Development of a wearable input device based on human hand-motions recognition

In this paper, a new wearable input device recognizing human hand-motion, a keyglove, is proposed. The glove can resolve the disadvantages of the conventional input devices and can be adapted to the mobile computing environment The device is applicable as the touch-typing input method for users' easy understanding and improvement of input speed. The hand-motion for touch-typewriting using QWERTY keyboard, which is most widely being used currently, is analyzed. The analyzed results show that the model with 21 DOF can be reduced to one with approximately 14 DOF. The hand-motion capture module using low price sensors is also developed for hand-motion recognition. In general, however, typists using the keyglove system can not exactly determine the key position of desired input letter because the virtual keyboard does not have the physical location of key layouts, and that causes many typewriting errors at a long typewriting time. Therefore, an algorithm is needed to cope with the problem and to reduce typewriting errors due to personal disparities such as hand shapes and typewriting habits. For this reason, the time-variant prediction algorithm is proposed to minimize typewriting errors, and the possibility of the developed keyglove system is also verified.