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Electroencephalogram (EEG) used simultaneously with video monitoring can record detailed patient physiology during a seizure to aid diagnosis. However, current patient monitoring systems typically require a patient to stay in view of a fixed camera limiting their freedom of movement. The goal of this project is to design an automatic

Electroencephalogram (EEG) used simultaneously with video monitoring can record detailed patient physiology during a seizure to aid diagnosis. However, current patient monitoring systems typically require a patient to stay in view of a fixed camera limiting their freedom of movement. The goal of this project is to design an automatic patient monitoring system with software to track patient movement in order to increase a patient's mobility. This report discusses the impact of an automatic patient monitoring system and the design steps used to create and test a functional prototype.
ContributorsBui, Robert Truong (Author) / Frakes, David (Thesis director) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2014-05
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Description
Neurological disorders are the leading cause of physical and cognitive declineglobally and affect nearly 15% of the current worldwide population. These disorders include, but are not limited to, epilepsy, Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis. With the aging population, an increase in the prevalence of neurodegenerative disorders is expected. Electrophysiological monitoring of

Neurological disorders are the leading cause of physical and cognitive declineglobally and affect nearly 15% of the current worldwide population. These disorders include, but are not limited to, epilepsy, Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis. With the aging population, an increase in the prevalence of neurodegenerative disorders is expected. Electrophysiological monitoring of neural signals has been the gold standard for clinicians in diagnosing and treating neurological disorders. However, advances in detection and stimulation techniques have paved the way for relevant information not seen by standard procedures to be captured and used in patient treatment. Amongst these advances have been improved analysis of higher frequency activity and the increased concentration of alternative biomarkers, specifically pH change, during states of increased neural activity. The design and fabrication of devices with the ability to reliably interface with the brain on multiple scales and modalities has been a significant challenge. This dissertation introduces a novel, concentric, multi-scale micro-ECoG array for neural applications specifically designed for seizure detection in epileptic patients. This work investigates simultaneous detection and recording of adjacent neural tissue using electrodes of different sizes during neural events. Signal fidelity from electrodes of different sizes during in vivo experimentation are explored and analyzed to highlight the advantages and disadvantages of using varying electrode sizes. Furthermore, the novel multi-scale array was modified to perform multi-analyte detection experiments of pH change and electrophysiological activity on the cortical surface during epileptic events. This device highlights the ability to accurately monitor relevant information from multiple electrode sizes and concurrently monitor multiple biomarkers during clinical periods in one procedure that typically requires multiple surgeries.
ContributorsAkamine, Ian (Author) / Blain Christen, Jennifer (Thesis advisor) / Abbas, Jimmy (Committee member) / Muthuswamy, Jitendran (Committee member) / Goryll, Michael (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2024