A novel approach of prosthetic arm control using computer vision, biosignals, and motion capture

Modern day prosthetics are traditionally controlled using EMG readings, which allow the user to control a limited number of degrees of freedom at one time. This creates a serious disadvantage compared to a biological arm because it constrains the fluid motion and dynamic functionality of the device. We present a novel architecture for controlling a transhumeral prosthetic device through the combination of several techniques, namely computer vision algorithms operating on “eye gaze” data, traditional prosthetic control methods, and the operator´s motion capture data. This sensor fusion allows the prosthetic device to locate itself in a 3D environment as well as the locations of objects of interest. Moreover, this architecture enables a more seamless motion and intuitive control of the prosthetic device. In this paper, we demonstrate the feasibility of this architecture and its implementation with a prototype.