Wheelchair Movements Control Using Eog

Abstract

The number of disabled people is rapidly increasing, with the most common cause being the inability to control limbs as a result of an accident is the immobility's root cause. The inability to move impedes the people from their daily routines as well as makes them socially isolated. We will discuss in this paper about the wheelchair prototype model where the movement is controlled by EOG, a type of electro-physiological signal, generated by eye movements. The proposed prototype's performance is evaluated on its efficiency and accuracy. The proposed prototype is cost efficient because EOG signal acquisition is very simple and economical. One of the key techniques of the method is the acquisition of EOG signals. This paper describes an effective auxiliary method for mobilization, in order to improve the standard of living of people who are afflicted with quadriplegic in particular. These people rely on others for survival on most of the time for mobility. This product includes EOG acquisition, amplification, and digitalization, and feature extraction, separation of signals, normalization and wheelchair movement control. Python is used in signal analysis and control. Python is also light, which reduces the amount of computing hardware required.