Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 41 for “"Bioelectrical and Neuroengineering"”.
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Characterizing Neurotransmitter Receptor Activation with a Perturbation Based Decomposition Method
… receptor activation can be used in the diagnosis and study of neurological disorders. Single-unit recordings provide a method of measuring postsynaptic potentials in neurons using a microelectrode system, but yield no detailed information regarding the neurotransmitter receptors that contribute to …
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Implementation of Novel Group Delay Decomposition Method and Surgical Protocol for Assessing Peripheral Neuropathy
… paper outlines a surgical procedure for exposing and stimulating the sciatic nerve of an anesthetized rodent for purposes of obtaining conduction velocity readings. The ability to accurately quantify nerve conduction velocity has potential for use in the field of diagnostic medicine and disease …
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Using convolutional neural networks for fine grained image classification of acute lymphoblastic leukemia
… blood smear. During examination, lymphocytes and other white blood cells (WBCs) are distinguished from abnormal lymphoblasts through fine-grained distinctions in morphology. Manual microscopy is a slow process with variable accuracy that depends on the laboratorian's skill level. Thus …
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Analysis of Eye Movements to Cartoon Faces in Videos
… are indicative of how we direct our attention and therefore play a role in memory and cognition. For static images, it is established that saccades move faster to faces compared to other objects. We hypothesize that the same is true for videos. To test this hypothesis, saccades to faces in …
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Improving Golf Putt Performance with Statistical Learning of EEG Signals
… correlation coefficient, power spectrum density and coherence, which are used as features for the classification algorithm. To predict golfers' performance, the support vector machine algorithm is used to classify the EEG patterns into two categories corresponding to successful and non-successful …
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fMRI assessment of ischemic stroke in humans
… blood flow is insufficient to the metabolic demand of brain. The lack of oxygen supply will directly lead to the death of brain tissue. There are two major injury regions: the infarct and penumbra. Mostly, since the infarct regions became dead tissues rapidly after stroke, there is a tiny …
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Neuro-Silicon Interface of a Hirudo medicinalis Retzius Cell Integrated with Field Effect Transistor
… of neurology, neuroscience, electrophysiology and cellular biology. In previous work by Peter Fromherz, single neurons were successfully coupled to transistors [1]. This thesis aims to show proof of concept of the fabrication of a simple neuro-silicon interface using wafer processing methods …
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Identifying and Predicting Rat Behavior Using Neural Networks
… role in episodic memory function. Understanding the relation between electrophysiological activity in a rat hippocampus and rat behavior may be helpful in studying pathological diseases that corrupt electrical signaling in the hippocampus, such as Parkinson’s and Alzheimer’s. Additionally, …
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Characterization of the high frequency alternating current block in the rat sciatic nerve using cuff electrodes and macro-sieve electrodes
… cuff electrodes were designed, fabricated and non-chronically implanted in the sciatic nerve of two-month-old Lewis rats. A proximal constant current stimulus to the nerve was blocked by applying a high frequency sinusoidal signal to the distally placed tripolar cuff electrode. The …
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Modulation of motor learning with high-intensity transcranial electric stimulation
… match the higher magnitudes used in animal and <em>in vitro</em> studies and subsequently yield more robust effects. As done commonly in the literature, we targeted the motor cortex (M1), specifically in the context of neuroplastic changes taking place during motor learning in healthy adult …
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tDCS effects on synaptic plasticity and motor skill learning
… scalp. Its potential to enhance brain function and treat brain-related disorders has led to its increasing popularity due to its safety, simplicity, and affordability. However, its effectiveness remains a topic of debate.</p>
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A novel visual stimulation paradigm: exploiting individual primary visual cortex geometry to boost steady state visual evoked potentials (SSVEP)
… We found that by dividing the annulus into standard octants, flickering upper horizontal octants with opposite temporal phase to the lower horizontal ones, and left vertical octants opposite to the right vertical ones, the normalized SSVEP power was enhanced by 202% relative to the …
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Wearable Disposable Elecetrotherapy
… addiction, cognitive decline, wound healing, and drug delivery. However, patient compliance remains low due to the high initial cost, cumbersomeness and inconvenience of existing technology compared to pharmaceuticals. Current electrotherapy devices are often bulky and require users to connect …
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Translational Modeling of Non-Invasive Electrical Stimulation
… on-going as are mechanistic studies both in vivo and in vitro. Volume conduction models are being applied to these areas of research, especially in the design and analysis of clinical montages. However, additional research on the parameterization of models remains.</p> <p>In this dissertation, …
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Investigation of a Simulated Annealing Cooling Schedule Used to Optimize the Estimation of the Fiber Diameter Distribution in a Peripheral Nerve Trunk
… annealing. This paper explores the structure and behavior of simulated annealing for the application of optimizing the group delay estimated fiber diameter distribution. Specifically, a set of parameters known as the cooling schedule is investigated to determine its effectiveness in the …
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Finding a Viable Neural Network Architecture for Use with Upper Limb Prosthetics
… of if it’s possible to produce a simple, quick, and accurate neural network for the use in upper-limb prosthetics. Through the implementation of convolutional and artificial neural networks and feature extraction on electromyographic data different possible architectures are examined with regards …
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Modeling Action Potential Propagation During Hypertrophic Cardiomyopathy Through a Three-Dimensional Computational Model
… (HCM) is the most common monogenic disorder and the leading cause of sudden arrhythmic death in children and young adults. It is typically asymptomatic and first manifests itself during cardiac arrest, making it a challenge to diagnose in advance. Computational models can explore and reveal …
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Perturbation Based Decomposition of sEMG Signals
… unit action potentials in terms of amplitude and firing times is useful for clinical research as well as diagnosis of neurological disorders. Successful decomposition of sEMG signals would allow for pertinent motor unit action potential information to be acquired without discomfort to the …
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Effects of weak electric fields on long-term synaptic plasticity
… in the use of tDCS for treating brain disorders and improving brain function. However, the effects of tDCS have been highly variable across studies, leading to a debate over its efficacy. A major challenge is therefore to design tDCS protocols that yield predictable effects, which will require a …
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