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https://hdl.handle.net/10356/72775
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DC Field | Value | Language |
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dc.contributor.author | Oh, Yoke Chew | |
dc.date.accessioned | 2017-11-13T12:45:41Z | |
dc.date.available | 2017-11-13T12:45:41Z | |
dc.date.issued | 2017 | |
dc.identifier.uri | http://hdl.handle.net/10356/72775 | |
dc.description.abstract | Past studies had shown promising results of Electroencephalography(EEG) based BCI as tool for communication and control. Several channels of BCI such as motor imagery, steady state visual evoked potential and visual spatial attention had been proposed. In this project, the goal was to demonstrate EEG-based control to a robotic device (SPHERO) using a covert visual spatial attention task. Specifically, it used the alpha and beta band neural oscillations observed during the task as input features for training of model. Band power of those neural oscillation were used to train a Linear Discriminant Analysis model. Average validation accuracy of 72.5% and average test accuracy of 60.9% were obtained from five subjects. A decreased in accuracy was attributed to feature shift due to non-stationarity of features and increasing fatigue level. Future designs for BCI could explore ways to minimised fatigue induced during the course of experiment and adapt the classifier to account for feature shifts | en_US |
dc.format.extent | 32 p. | en_US |
dc.language.iso | en | en_US |
dc.rights | Nanyang Technological University | |
dc.subject | DRNTU::Engineering::Computer science and engineering | en_US |
dc.title | Visual target selection using brain signals acquired using Electroencephalography (EEG) | en_US |
dc.type | Final Year Project (FYP) | en_US |
dc.contributor.supervisor | Smitha Kavallur Pisharath Gopi | en_US |
dc.contributor.school | School of Computer Science and Engineering | en_US |
dc.description.degree | Bachelor of Engineering (Computer Engineering) | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | restricted | - |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
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Oh_Yoke_Chew_FYP_Report.pdf Restricted Access | 1.27 MB | Adobe PDF | View/Open |
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