Gesture recognition of air-tapping and its application to character input in VR space

Abstract

The motion of the finger is made up of a combination of forearm part (extrinsic) muscles and hand part (intrinsic) muscles. We have created a wearable fingerless glove controller to sense sEMG(surface Electromyography) from intrinsic muscles using dry electrodes [Tsuboi et al. 2017]. Recognition of air-tapping gesture with a sensor attached to wearable finger-less glove controller is a challenging problem. In this study, we focused on motion recognition of air-tapping and performed motion recognition using CNN and evaluated its accuracy. As a result, the accuracy in intra-subject identification was 85.05%. Also, experiments are currently being conducted in anticipation of character input in VR space [Grubert et al. 2018]. Character input experiment in VR space was carried out using sEMG wearable fingerless glove controller, as a primitive experiment of the use of sEMG glove in VR space. Based on the results, we discussed the efficiency of character input using sEMG glove in VR space.