Design and Development of an Engineering Application Control Using Brain Signal

Chan, Kee Sum (2016) Design and Development of an Engineering Application Control Using Brain Signal. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

Controlling the application by using our brain signal is the trend will drive the future of technology. Many people are paralyzed by a spinal cord injury and they have to live confined to a wheelchair in the rest of their life. However, they can blink their eyes to communicate or answering simple questions. The eye related signals will be predominant in the frontal and prefrontal regions of the brain and the mind-controlled robotic exoskeleton being developed by EU-funded researchers could help them get out of this corner. This project describes the development of a method to analyze and classify the electroencephalography (EEG) signal generated using eye blinking so that it could turn into a useful signal to control the engineering applications. A bandpass filter was used to filter the noise and a method for measuring and detecting using kurtosis based Independent Component Analysis were used in this project to analyze the EEG signal. The peak detection algorithm and thresholding method used to classify the data. Instead of using one electrode’s channel to classify the data, four different electrode’s channels, AF3, AF4, F7 and F8 were used by comparing their features to determine the user’s signals. After the experiments, for 10 different data, left eye blinking, right eye blinking, combination of left and right eyes blinking and both eyes closed and each data contain 3 to 5 real signals, it shows a 78% of accuracy to classify the user signal correctly. Thus, it is for those who paralyzed or stroke patient to control some application by blinking their eyes.