Volitional control of prostheses is most commonly achieved by myoelectric signalling. The electromygraph (EMG) is detected and processed by a controller, that decodes and relates the signal to the corresponding position of the prosthetic. Myoelectric signalling is limited in users by 2 factors: lack of nerve endings corresponding to the position of the amputation, and neurological damage resulting in poor signal control. In this paper, we propose a means of overcoming the computer vision overhead by use of in-vivo retinal signalling to complement EMG for improved control. This is demonstrated using a real-time conductance-based simulator as the sole method of control for an upper-limb prosthesis. Input image streams are received by a camera and used to activate the combined rod and cone photoreceptor cell responses. This in turn generates a spike train which is counted and averaged over time, and passed to an Arduino-based control system which modulates the behavior of the prosthesis. We seek to use this system to lower the experimental barriers of in-vivo ganglion electrical signalling by presenting a way to use retina emulation. A link to the simulator is provided.