Performance analysis of an electrooculography-based on intelligent wheelchair motion control

The aim of this study is to analyse the performance of fuzzy logic-based control designed for a wheelchair motion control using the eye movement signals. These signals are acquired through electrooculography (EOG) technique. The EOG is a technique to acquire the eye movement signals from a person, i.e tetraplegia, which the data obtained can be used as a main communication tool, for example in wheelchair motion control. In this project, the eye movement signals were classified using the fuzzy classifier (FC). Then, the PD-type fuzzy controller was successfully designed and tested on the wheelchair model, for wheelchair motion control. The wheelchair model system was developed using MSC. Visual Nastran. The eye movement signals that acquired through the EOG technique is acted as a motion input references. The simulation results obtained show that the PD-type fuzzy logic controller designed has successfully managed to track the input reference for linear motion set by the EOG signal. In this paper, the simulation results are focused for backward motion only.