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Title: Improved brain-computer interface methods with application to gaming
Author: Henshaw, James
ISNI:       0000 0004 7226 4603
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2017
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Brain-computer interfaces (BCIs) are real-time communication systems which bridge the gap between human and machine, extracting useful neural signals from the brain and converting them into commands which allow the user to interact with computers or devices using their thoughts. BCIs have a wide range of applications, including gaming, research and entertainment. And they can also be used as part of an assistive device for disabled users. This PhD thesis focuses on two BCI types: the steady-state visually evoked potential (SSVEP) BCI, which is operated using gaze control, and the motor imagery-based BCI, which responds to imagined limb movements. Contained within are novel methods designed to improve each BCI type with respect to performance and user experience. New normalisation methods are found to improve SSVEP-BCI performance. A new three-dimensional SSVEP-BCI game is created, along with the Predicted Optimal Colour (POC) SSVEP-BCI, which automatically selects the optimal stimulus colours for a user in order to exploit differences in the way the brain responds to different coloured stimuli. And a feasibility study is conducted where we implement a new method for training users to operate a motor imagery-based BCI, and investigate predictors of BCI performance.
Supervisor: Liu, Wei ; Romano, Daniela Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available