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http://hdl.handle.net/11375/22894
Title: | Advances in EP and ERP signal processing |
Authors: | Chrapka, Philip |
Advisor: | de Bruin, Hubert Reilly, Jim |
Department: | Electrical and Computer Engineering |
Publication Date: | 2018 |
Abstract: | Our understanding of brain function is still very limited. Much research is being conducted to further our understanding and develop new treatments, diagnostics and devices that not only could be more effective in helping us deal with neurological and psychiatric disorders and rehabilitation, but also make cognitive enhancement possible. However, none of this is possible without signal processing capabilities to extract information from electroencephalography (EEG) signals and especially event related potentials (ERPs) and evoked potentials (EPs). This thesis presents new developments in EP artifact rejection, ERP brain source localization and dynamic causal brain network estimation during an ERP. Chapter 2 presents a new method for reducing contamination from compound muscle action potentials (CMAPs) recorded along with EEG activity during repetitive transcranial magnetic stimulation (rTMS). This development improves the visibility of short latency cortical activity as a result of rTMS. In the application of brain source localization methods, especially beamforming, head modelling errors can cause significant performance degradation. The robust minimum variance beamformer (RMVB) developed in Chapter 3 improves beamformer performance relative to the MVB and its regularized and eigenspace variations in the face of these head modelling errors. The RMVB specifically optimizes for the worst-case estimate of the uncertainty. Lastly, Chapter 4 describes the Adaptive Sparse ERP Tracking (ASET) algorithm for estimating dynamic and causal networks that are involved in processing ERPs. The ASET algorithm is applied to investigate the dynamics in auditory processing, specifically resulting from the β-band and its envelope. |
URI: | http://hdl.handle.net/11375/22894 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Chrapka_Philip_K_201804_PhD.pdf | 4.3 MB | Adobe PDF | View/Open |
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