Author, Institution: Mohammad Shahbakhti, Kaunas University of Technology
Science area, field of science: Technological Sciences, Electrical and Electronics Engineering, T001
Scientific Supervisor: Prof. Dr. Vaidotas Marozas (Kaunas University of Technology, Electrical and Electronics Engineering, T001)
Dissertation Defense Board of Electrical and Electronics Engineering Science Field:
Prof. Dr. Elena Jasiūnienė (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering, T001) – chairperson
Prof. Dr. Piotr Durka (University of Warsaw, Poland, Technological Sciences, Electrical and Electronics Engineering, T001)
Prof. Dr. Dangirutis Navikas (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering, T001)
Prof. Dr. Aušra Saudargienė (Lithuanian University of Health Sciences, Natural Sciences, Biophysics, N011, Informatics, N009)
Prof. Dr. Algimantas Valinevičius (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering, T001)
Dissertation defense meeting will be at Rectorate Hall of Kaunas University of Technology (K. Donelaičio 73-402, Kaunas)
The doctoral dissertation is available at the library of Kaunas University of Technology (Gedimino 50, Kaunas) and on the internet: M. Shahbakhti el. dissertation (PDF)
Annotation: Consciousness is a multifaceted construct that spans a continuum from wakefulness—characterized by responsiveness to external stimuli and cognitive engagement—to altered states, such as fatigue, sleep, and anesthesia, where individuals may experience decreased cognitive function or difficulty being easily aroused. Given its wide range of real-life applications and its origin in brain, a significant amount of research has focused on studying consciousness using brain imaging techniques, particularly electroencephalography (EEG). However, most studies have relied on conventional multichannel EEG systems, which, while effective, are expensive and impractical for daily use by individuals. This thesis aims to develop EEG-based algorithms for monitoring consciousness levels in real-world applications, focusing on low-cost portable EEG devices that offer a more accessible solution for widespread use outside of laboratories and controlled environments. The central research question investigates how the limitation of spatial coverage in single channel EEG recordings can be compensated to capture changes in consciousness levels. The working hypothesis suggests that decomposing a single EEG signal into its sub-bands and applying nonlinear analysis can overcome these limitations by capturing distinct neural dynamics associated with different consciousness levels. By focusing on low-cost portable EEG devices, this work advances the field of EEG-based consciousness monitoring, making it more applicable for everyday use and accessible to a broader population.
October 22 d. 10:00
Rectorate Hall at Kaunas University of Technology (K. Donelaičio 73-402, Kaunas)
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