Facial electromyogram-based facial gesture recognition for hands-free control of an AR/VR environment: optimal gesture set selection and validation of feasibility as an assistive technology.

ABSTRACT: The rapid expansion of virtual reality (VR) and augmented reality (AR) into various applications has increased the demand for hands-free input interfaces when traditional control methods are inapplicable (e.g., for paralyzed individuals who cannot move their hands). Facial electromyogram (fEMG), bioelectric signals generated from facial muscles, could solve this problem. Discriminating facial gestures using fEMG is possible because fEMG signals vary with these gestures. Thus, these signals can be used to generate discrete hands-free control commands. This study implemented an fEMG-based facial gesture recognition system for generating discrete commands to control an AR or VR environment. The fEMG signals around the eyes were recorded, assuming that the fEMG electrodes were embedded into th

SUBMITTER: Kim C 

PROVIDER: S-EPMC10382369 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature