Generative Adversarial Networks for Localized Vibrotactile Feedback in Haptic Surfaces

Touch-screens are the most relevant interface in the context of human-computer interaction. Moreover, they are widely used as interaction means for digital musical instruments, where a complex action-perception loop is involved in the user experience. This is why reestablishing a rich vibrotactile feedback is of key importance for improving the quality of the user's interaction. To the knowledge of the authors, this paper presents the first experiments with Generative Adversarial Networks (GANs) to generate time-reversed signals that can be used to create localized vibrotactile feedback over a rigid surface. The generated signals are sent into an experimental setup and a vibration scan is carried out. A localized peak generated with a signal synthesized by the trained GAN model is observed and studied. Later, different metrics are proposed to evaluate the quality of the generated samples and the obtained localized peak. Finally, a preliminary evaluation of the feasibility of this approach to generate localized vibrations in the range of 200 - 300 Hz for touch -screen applications is discussed.