Bug algorithm to guide wheelchair motion based on offline electro-oculography signals

• Main Author: Al-Haddad, Anwar Ahmed Hussein
• Format: Thesis
• Language: English
• Published: 2013
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/42075/1/AnwarAhmedHusseinAl-HaddadMFKE2013.pdf; http://eprints.utm.my/id/eprint/42075/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:77708?queryType=vitalDismax&query=Bug+algorithm+to+guide+wheelchair+motion+based+on+offline+electro-oculography+signals&public=true

Certain disabled persons are not able to control the common powered wheelchair using joystick due to their limb movement restrictions. Hence, lots of current researches have studied other alternatives to control the powered wheelchair. Electrooculography (EOG) eye tracking control is one of the most ordinary alternative means to control the wheelchair because it offers a more natural mode to guide the wheelchair. Yet, it cannot be realized because users are normally not allowed to look around the surrounding environment during wheelchair motion. This is because the eye movements control the wheelchair while the user needs to look up to move forward, right to turn right, left to turn left and down to stop the wheelchair. In addition, this method exhausts the user due to the concentration needed during the navigation process. In this study, an automatic navigation approach alongside the manual method is proposed to guide the wheelchair by means of offline EOG signal. The automatic mode navigates the wheelchair from initial point to goal point while avoiding obstacles by employing Bug2 algorithm. Bug algorithms guide the robot from its starting point towards a preset goal point and avoid obstacles detected by sensors, and they do not require any other information about the environment in the navigation process. The EOG signals are measured, recorded, and analyzed using a biomedical measurement system (KL-720). The desired goal point direction and distance are calculated by analyzing horizontal and vertical gaze angles obtained. The hardware of the powered wheelchair is developed and modified so that it can be controlled automatically using EOG signal. The simulation done showed that Bug algorithms are able to guide the wheelchair to the desired destination based on only EOG signal. The new technique allows the user to look around without restraints, while the wheelchair is navigated automatically to the desired goal point