Simulation of Eye Tracking Control based Electric Wheelchair Construction by Image Segmentation Algorithm

Abstract

In this fast-paced world, it is very challenging for the elderly and disabled population to move independently to their desire places at any convenient time. Fortunately, some of the people have good eyesight and physically strong to take care of their survival. Nevertheless, Electric wheelchair (EWC) can provide them a better lifestyle with commendable confidence. At the same time, the hand, head and voice recognition-based EWC meet many limitations. Despite, the eye-tracking-based EWC provides a better smartness in their lifestyle. This research article discusses better accuracy achievement and minimizes the delay response time in the proposed system. The proposed eye-tracking EWC is differed from another existing system with good validation parameters of the controller and it introduces edge detection to identify the eye pupil position in the face. The proposed method includes a PID controller to control the DC motor, which in turn controls the rotation of wheel in EWC. This research article is mainly focused on the cost-effectiveness and improvement in the system performance. The display system is mounted in front of the sitting position of EWC users. The camera captures eye pupil position and it determines the direction of the EWC movement by controlling DC motor with the help of a PID controller. When derivative (D) control is used in the proposed system, the system response is quite faster and it reduces the delay time between the user and system reaction. This pupil of eye position is determined by a canny edge detector, which provides good results when compared with other edge detection approaches. Object detection in front of the EWC is an added advantage of the proposed system. The proposed article integrates all the activities and measures the system performance. The proposed model achieves an accuracy of about 90% and response time is least compared with the existing methods.