Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.690831
Title: Eye tracking with EEG life-style
Author: Haji Samadi, Mohammad Reza
ISNI:       0000 0004 5915 6202
Awarding Body: University of Birmingham
Current Institution: University of Birmingham
Date of Award: 2016
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Abstract:
Innovative human-computer interaction paradigms with minimum motor control provide realistic interactions and have potential for use in assistive technologies. Among the human modalities, the eyes and the brain are the two modalities with minimum motor requirements. Most of the existing assistive technologies based on tracking the eyes (such as electrooculography and videooculography) are intrusive, limited to the laboratory environment and restrictive or are not accurate enough for real-life applications. The same limitations apply to brain activity monitoring systems such as electroencephalography (EEG). In this research, the objective is to employ a less-intrusive, consumer-grade EEG headset designed for mobile applications to track the user’s eyes and reliably estimate focus of foveal attention (FoA). To this end, signal processing approaches are proposed in order to classify different types of eye movements and estimate FoA. The FoA estimation is then improved using the brain responses to flickering stimuli recorded in EEG data. Afterwards, the FoA estimation is again improved by proposing an automated method to remove eye-related artefacts from brain responses to the stimuli. Finally, the FoA estimation is best improved by extracting eye-movement classification and brain-response detection features from EEG data projected into independent sources.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.690831  DOI: Not available
Keywords: TA Engineering (General). Civil engineering (General)
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