A Controller tor Assistive Devices using Eye Movement and Electroeneephalography
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Date
2018
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Uva Wellassa University of Sri Lanka
Abstract
Assistive technology is adapted or specially designed technology for improving the
functioning of people with disabilities. However, access to assistive technology is
limited in Sri Lanka. The high cost of assistive technology development has put
them out of reach of most of the disabled Sri Lankans. Therefore, low-cost
equipment to read signals from patients with limited abilities will lead this
technology development to next level. This research presents the development of a
low-cost system which acquires and process brainwaves and eye movements of
individuals. These signals are processed for controlling few assistive devices.
Further, the research explores methods for using the system in aids with the brain's
ability to undergo plastic changes for the recovery of function and to ensure
patient's safety. Experiments in this project revealed different ways of brainwave
processing and meaningful brainwave output frequencies to identify more emotions
and motives of human brain like levels of concentration and drowsiness. The tests
were performed on different subjects and revealed many new useful results such as
suitable positions to place the electrode, variations in results when the subject gets
familiar with the system. Hough transformation based eye tracking system is
developed to detect iris position. Initially, it is implemented in MATLAB to detect
three iris positions, left, right and center within 4-5 seconds. Later, the system is
implemented on Raspberry-Pi using Open CV and Python with less than 3 seconds
detection time. Finally, this research concludes that incorporating eye iris
movement tracking with brainwave can be used as a novel low-cost approach. This
combination allows developing a simple real time assistive device controller. This
system can be used as a solution for connecting physically disabled individuals in
developing countries to smart assistive devices.
Keywords: Brainwaves, Eye movements, Hough transformation, Assistive technology,
Electroencephalography
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Mechanical Engineering, Computer Science