Proportional Myoelectric Control in a Virtual Reality Environment

Translating input modalities such as hand interactions, speech, and eye tracking in virtual reality offers an immersive user experience. Especially, it is crucial to track the user’s hand gestures, since they can help in translating user intentions into actions in virtual environments. In this work, we developed a virtual reality application which incorporates electromyography-based deep learning methods for recognizing and estimating hand movements in an online fashion. Our application automates all user controls, providing an immense potential for rehabilitation purposes.