Design a neurofeedback system with incorporated real time EOG artifact removal
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 th...
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| Format: | Final Year Project / Dissertation / Thesis |
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2022
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| Online Access: | http://eprints.utar.edu.my/4907/1/fyp_EE_HJL_2022.pdf http://eprints.utar.edu.my/4907/ |
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| _version_ | 1833428727901454336 |
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| author | Ho, Jun Leong |
| author_facet | Ho, Jun Leong |
| author_sort | Ho, Jun Leong |
| building | UTAR Library |
| collection | Institutional Repository |
| content_provider | Universiti Tunku Abdul Rahman |
| content_source | UTAR Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | 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 |
| format | Final Year Project / Dissertation / Thesis |
| id | my-utar-eprints.4907 |
| institution | Universiti Tunku Abdul Rahman |
| publishDate | 2022 |
| record_format | eprints |
| spelling | my-utar-eprints.49072022-12-29T12:19:14Z Design a neurofeedback system with incorporated real time EOG artifact removal Ho, Jun Leong T Technology (General) TK Electrical engineering. Electronics Nuclear engineering TR Photography 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 2022-04 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/4907/1/fyp_EE_HJL_2022.pdf Ho, Jun Leong (2022) Design a neurofeedback system with incorporated real time EOG artifact removal. Final Year Project, UTAR. http://eprints.utar.edu.my/4907/ |
| spellingShingle | T Technology (General) TK Electrical engineering. Electronics Nuclear engineering TR Photography Ho, Jun Leong Design a neurofeedback system with incorporated real time EOG artifact removal |
| title | Design a neurofeedback system with incorporated real time EOG artifact removal
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| title_full | Design a neurofeedback system with incorporated real time EOG artifact removal
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| title_fullStr | Design a neurofeedback system with incorporated real time EOG artifact removal
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| title_full_unstemmed | Design a neurofeedback system with incorporated real time EOG artifact removal
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| title_short | Design a neurofeedback system with incorporated real time EOG artifact removal
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| title_sort | design a neurofeedback system with incorporated real time eog artifact removal |
| topic | T Technology (General) TK Electrical engineering. Electronics Nuclear engineering TR Photography |
| url | http://eprints.utar.edu.my/4907/1/fyp_EE_HJL_2022.pdf http://eprints.utar.edu.my/4907/ |
| url_provider | http://eprints.utar.edu.my |