Masters Thesis

A Steady-state Visually Evoked Potential Based Brain Computer Interface Approach and Its Applications

A Brain-Computer Interface (BCI) provides an interaction between a brain and a device that enables the electroencephalography (EEG) signals from the scalp of the person to control an external device, such as operations of an electric wheelchair, electronic devices, etc. This study provides a Steady State Visually Evoked Potential (SSVEP) based BCI system to control the operation of an electric wheelchair by using the EEG signals obtained from the brain. the main objective is to process the EEG signals obtained from an externally driven stimulus and trigger the control signals to operate the electric wheelchair. by providing attention to the external visual stimulus, corresponding EEG signals are elicited from the visual cortex region of the brain. the obtained EEG signals are classified at different frequencies using signal processing algorithms and given as an input to the BCI system, which controls the operation of an external device (electric wheelchair). the proposed application provides a platform for the individuals suffer from Neuromuscular Degenerative Diseases (NMDs) such as Amyotrophic Lateral Sclerosis (ALS), Locked-In Syndrome (LIS), etc., and help them to lead an independent life. Four trials have been performed to measure the accuracy and reliability of the system. Also, the proposed paradigm is compared with the Audio Steady State Response (ASSR) approach.

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