E.O.G. guidance of a weelchair using spiking neural networks

In this paper we present a new architecture of spiking neural networks (SNNs) to control the movements of a wheelchair. In this case, to send different commands we have used electrooculography (EOG) techniques, so that, control is made by means of the ocular position (eye displacement into its orbit). Spatiotemporal coding that combines spatial constraints with temporal sequencing is of great interest to visual-like circuit model. Therefore, a neural network (SNN) is used to identify the eye model, therefore the saccadic eye movements can be detected and know where user is looking at. The system consists of a standard electric wheelchair with an on-board computer, sensors and graphical user interface running on a computer.