Development of intelligent control of wheelchair for tetraplegia - Nurul Muthmainnah Mohd Nor (Kulliyyah of Engineering, International Islamic University Malaysia, 2012)
Tetraplegia is a paralysis that is caused by serious injuries or illness to a human that lead to a partial or total loss of their lower limb and torso. A person who has such paralysis is highly dependent on an assistant and a wheelchair for mobility. The wheelchair has become a main mean of transport for mobility for them as well as among elderly or disabled people. It is not always the case where the helper or assistant is available with them all the time; therefore independence is encouraged among wheelchair users. To encourage independence, their potential and level capability can be fully utilized, for example in the case of tetraplegia. Their movement is very limited, such that they are mostly capable to move their eye muscles. It is noted that eye movement technique is a very significant communication tool for a tetraplegia. In this research, the eye movement signal of tetraplegia is used to control the wheelchair motion. This signal that is called electrooculogram and it can be generated at different eye movements' directions and levels. The electrooculography (EOG) is a bio-potential signal which is derived from the polarization potential and recorded from the skin in the vicinity of the eyes. The, g.USBamp from G.TEC Medical Engineering GMBH is used to collect the eye movement signal data by using Ag/AgCl electrodes and the data is passed to MATLAB/SIMULINK software for data analysis and signal processing. Analysis on different directions and strength level is studied and fed to a virtual wheelchair model. Investigation on different EOG signals obtained from four different places around eye (right, left, up, and down) has been done. It shows that different signal levels have different strength of EOG signals. Fuzzy classifier has been designed to determine the corresponding level of input set point for distance and angle. Simulation exercises has verified that different strength of eye movement signals can be used for helping the tetraplegia in their mobility using wheelchair, which is used as a set point for wheelchair motion control. For motion control, an intelligent control technique based on fuzzy logic controller was designed and developed. The controller is integrated in simulation with the wheelchair model for validation on the wheelchair system performance. The result shows that, the wheelchair system is capable of responding to have different distances or angle based on different eye movement input data. Hardware implementation has been constructed and the controller as been tested experimentally. Results have verified that the controller enables to achieve the desired input with good system performance. Therefore, the fuzzy logic controller designed has been able to control both the wheelchair model and real wheelchair system.