Development of Seamless Telepresence Robot Control Methods to Interact with the Environment Using Physiological Signals

Abstract

Current assistive devices to help disabled people interact with the environment are complicated and cumbersome. Our approach aims to solve these problems by developing a compact and non-obtrusive wearable device to measure signals associated with human physiological gestures, and therefore generate useful commands to interact with the smart environment. Our innovation uses machine learning and non-invasive biosensors on top of the ears to identify eye movements and facial expressions. With these identified signals, users can control different applications, such as a cell phone, powered wheelchair, smart home, or other IoT (Internet of Things) devices with simple and easy operations. Combined with VR headset, the user can use our technology to control a camera-mounted telepresence robot to navigate around the environment in the first-person's view (FPV) by eye movements and facial expressions. It enables a very intuitive way of interaction totally hands-free and touch-free.