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Design a neurofeedback system with incorporated real time EOG artifact removal

Ho, Jun Leong (2022) Design a neurofeedback system with incorporated real time EOG artifact removal. Final Year Project, UTAR.

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    Electroencephalography (EEG) is the electrophysiological, non-invasive method that can record the activities of the brain. It can use the electrodes that are attached to the scalp to detect the brain signal (Arefa Cassoobhoy, MD, MPH, 2020). Neurofeedback training (NFT) which is a training method that uses the Brain Computer Interface (BCI) to improve the cognition performance of the subjects. Artifacts in EEG are the signals not associated with the brain activities and these signals may affect the NFT process. So, it is important to remove artifacts from EEG signals. In our project, we will design a neurofeedback system to perform the real-time EOG artifact removal. The artifact removal is one of the pre-processing steps in the BCI system that removes the unwanted noise from the raw EEG signals. The method used for artifact removal is ICA-REG. the BCI system is designed by using the EMOTIV Insight headset to collect EEG signals, OpenViBE for processing the EEG signal, and the Unity3D application for the interface of the BCI system. We will use this BCI system to perform NFT for 6 subjects in 6 sessions and analyze the EEG data recorded from the subjects

    Item Type: Final Year Project / Dissertation / Thesis (Final Year Project)
    Subjects: T Technology > T Technology (General)
    T Technology > TK Electrical engineering. Electronics Nuclear engineering
    T Technology > TR Photography
    Divisions: Faculty of Engineering And Green Technology > Bachelor of Engineering (Honours) Electronic Engineering
    Depositing User: ML Main Library
    Date Deposited: 29 Dec 2022 20:19
    Last Modified: 29 Dec 2022 20:19
    URI: http://eprints.utar.edu.my/id/eprint/4907

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