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Scheduling Neural Sensors to Estimate Brain Activity

Abstract Research on developing new algorithms to improve information on brain functionality and structure is ongoing. Studying neural activity through dipole source localization with electroencephalography (EEG) and magnetoencephalography (MEG) sensor measurements can lead to diagnosis and treatment of a brain disorder and can also identify the area of the brain from where the disorder has originated. Designing advanced localization algorithms that can adapt to environmental changes is considered a significant shift from manual diagnosis which is based on the knowledge and observation of the doctor, to an adaptive and improved brain disorder diagnosis as these algorithms can track activities that might not be noticed by the human eye. An important ... (more)
Created Date 2012
Contributor Michael, Stefanos (Author) / Papandreou-Suppappola, Antonia (Advisor) / Chakrabarti, Chaitali (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Subject Biomedical engineering / Electrical engineering / biomedical signal processing / Dipole Source estimation / neural source estimation / particle filter / sensor scheduling / Wearable EEG
Type Masters Thesis
Extent 55 pages
Language English
Reuse Permissions All Rights Reserved
Note M.S. Electrical Engineering 2012
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis