In previous studies it was determined that the fiber diameter distribution in a peripheral nerve could be estimated by a simulation technique known as group delay. These results could be further improved using a combinatorial optimization algorithm called simulated 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 optimization process. Simulated annealing is a technique for finding the global minimum (or maximum) of a cost function which may have many local minima. The set of parameters which comprise the cooling schedule dictate the rate at which simulated annealing reaches its final solution. Converging too quickly can result in sub-optimal solutions while taking too long to determine a solution can result in an unnecessarily large computational effort that would be impractical in a real-world setting. The goal of this study is to minimize the computational effort of simulated annealing without sacrificing its effectiveness at minimizing the cost function. The cost function for this application is an error value computed as the difference in the maximum compound evoked potentials between an empirically-determined template distribution of fiber diameters and an optimized set of fiber diameters. The resulting information will be useful when developing the group delay estimation and subsequent simulated annealing optimization in an experimental laboratory setting.

Hypertrophic cardiomyopathy (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 underlying molecular mechanisms in cardiac electrophysiology by allowing researchers to alter various parameters such as tissue size or ionic current amplitudes. The goal of this thesis is to develop a computational model in MATLAB and to determine if this model can accurately indicate cases of hypertrophic cardiomyopathy. This goal is achieved by combining a three-dimensional network of the bidomain model with the Beeler-Reuter model and then by manually varying the thickness of that tissue and recording the resulting membrane potential with respect to time. The results of this analysis demonstrated that the developed model is able to depict variations in tissue thickness through the difference in membrane potential recordings. A one-way ANOVA analysis confirmed that the membrane potential recordings of the different thicknesses were significantly different from one another. This study assumed continuum behavior, which may not be indicative of diseased tissue. In the future, such a model might be validated through in vitro experiments that measure electrical activity in hypertrophied cardiac tissue. This model may be useful in future applications to study the ionic mechanisms related to hypertrophic cardiomyopathy or other related cardiac diseases.

Peripheral arterial occlusive disease (PAOD) affects 8 to 12 million Americans over the age of 50. As the disease progresses, arterial occlusions arising from atherosclerotic lesions inhibit normal metabolic vasodilation in the peripheries, resulting in limb ischemia and claudication. Pharmacological and surgical treatments currently used to treat both the hemodynamic and pain symptoms associated with PAOD can involve adverse and potentially life-threatening side effects. Thus, there is a need for additional innovative therapies for PAOD. Neurostimulation has a known analgesic effect on both acute and chronic pain. Although the exact mechanisms remain under investigation, local vascular tone may be modulated by neurostimulation in addition to pain modulation. The Gate Control Theory proposes that electrical activation of mechanoreceptive afferent somatosensory nerves, specifically Aβ fibers, inhibits pain signaling to the brain by activating an inhibitory interneuron in the dorsal horn of the spinal cord which dampens signaling from afferent, C type peripheral nociceptor nerves. Interestingly, Aβ fiber activation may also inhibit norepinephrine release from sympathetic nerve terminals on efferent neurons by activating α-2 adrenergic receptors along the same dermatome, resulting in localized vasodilation in both limbs. Ultimately, electrical stimulation may decrease mean blood pressure and increase local blood flow. The focus of this study was to optimize protocols and perform a small scale clinical study to investigate hemodynamic and analgesic responses to neurostimulation during acute ischemia. We hypothesized that ganglial transcutaneous electrical neurostimulation (TENS) and interferential current (IFC) treatments would decrease pain perception and vascular resistance in the periphery in young, healthy subjects. We further hypothesized that IFC may have a greater hyperemic and analgesic effect on acute ischemia than TENS as its current waveform may be more efficient at overcoming skin impedance. Interestingly, we found trends suggesting that TENS and IFC may increase vascular resistance (VR) and have no noticeable analgesic effect, though TENS may have a slightly lower increase in VR associated with an increase in pain. Further work characterizing the hemodynamic effects of different stimulus waveforms is needed to inform future research into possible neuromodulation therapies for ischemic disease.

This work focuses on modeling a demyelinated Hodgkin and Huxley (HH) neuron with Simulated Program with Integrated Circuit Emphasis (SPICE) platform. Demyelinating disorders affect over 350,000 people in the U.S and understanding the demyelination process at the cellular level is necessary to find safe ways to treat the diseases [9]. Utilizing a previous SPICE model of an electrically small cell neuron developed by Szlavik [32], an extended core conductor myelinated neuron was produced in this work. The myelinated neuron developed has seven active Nodes of Ranvier (nodes) separated by a myelin sheath. The myelin sheath can be successfully modeled with a resistive and capacitive network known as internodes. Both the Nodes of Ranvier and internode equivalent circuits were implemented in P-SPICE sub-circuit library files. Properties of the neuron can be changed in the library files to simulate neurons of different electrical or geometric properties. Using the P-SPICE code developed in this work, a myelinated neuron’s action potential was simulated and the action potential at each node was recorded. The action potential at each node was uniform in amplitude and pulse width. The conduction velocity of the action potential was calculated to be 57.15 m/s. Demyelination can be modeled by decreasing the capacitance and increasing the resistance of the myelin [34]. Two demyelinated neuron models were simulated in this work. The first model had one internode segment demyelinated, and the second model was of three consecutive internode segments. The resulting conduction velocity was calculated for both simulations. For one and three internode segment demyelinated the conduction velocity was slowed to 44.15 m/s, and 27.15 m/s respectively. This model successfully showed that an HH neuron implemented in SPICE could show the effects of demyelination on conduction velocity The goal of this work is to develop a demyelinated neuron so that treatments for Multiple Sclerosis (MS) and other demyelinated neurons could be simulated to test various treatments’ effectiveness. A current treatment for MS is ion channel blockers. Future work would be to use this model to test current ion channel blocker therapy and to validate if such therapies alleviate conduction slowing.

Intuitive prosthetic control is limited by the inability to easily convey intention and perceive physical requirements of the task. Rather than providing haptic feedback and allowing users to consciously control every component of manipulation, relegating some aspects of control to the device may simplify operation. This study focuses on the development and testing of a control scheme able to identify object stiffness and regulate impedance. The system includes an algorithm to detect the apparent stiffness of an object, a proportional nonlinear EMG control algorithm for interpreting a user’s desired grasp aperture, and an antagonistically acting impedance controller. Performance of a testbed prosthetic simulation used to controllably extrude pastes of different properties from a compliant tube was compared to that of the non-dominant human hand. The paste volume extrusion error and response time to perform the task were recorded for comparison. Statistical analysis using (GEE) and (TOST) suggests the prosthetic controller and human hand performed similarly along these metrics. Performance differences in the trials were more strongly correlated to tube type and repetition block. The results suggest that the developed controller allows users to perform a controlled squeezing task at a level comparable to the human hand with minimal training. It also suggests that a priori stiffness estimation acquired through quick palpations may be sufficient for effective control during simple manipulation. The lack of a learning curve suggests that the development of systems that automatically control aspects of mechanical interaction may offer users more advanced control capabilities with low cognitive load.

Nanoparticles are often considered as efficient drug delivery vehicles for precisely dispensing the therapeutic payloads specifically to the diseased sites in the patient’s body, thereby minimizing the toxic side effects of the payloads on the healthy tissue. However, the fundamental physics that underlies the nanoparticles’ intrinsic interaction with the surrounding cells is inadequately elucidated. The ability of the nanoparticles to precisely control the release of its payloads externally (on-demand) without depending on the physiological conditions of the target sites has the potential to enable patient- and disease-specific nanomedicine, also known as Personalized NanoMedicine (PNM). In this dissertation, magneto-electric nanoparticles (MENs) were utilized for the first time to enable important functions, such as (i) field-controlled high-efficacy dissipation-free targeted drug delivery system and on-demand release at the sub-cellular level, (ii) non-invasive energy-efficient stimulation of deep brain tissue at body temperature, and (iii) a high-sensitivity contrasting agent to map the neuronal activity in the brain non-invasively. First, this dissertation specifically focuses on using MENs as energy-efficient and dissipation-free field-controlled nano-vehicle for targeted delivery and on-demand release of a anti-cancer Paclitaxel (Taxol) drug and a anti-HIV AZT 5’-triphosphate (AZTTP) drug from 30-nm MENs (CoFe2O4-BaTiO3) by applying low-energy DC and low-frequency (below 1000 Hz) AC fields to separate the functions of delivery and release, respectively. Second, this dissertation focuses on the use of MENs to non-invasively stimulate the deep brain neuronal activity via application of a low energy and low frequency external magnetic field to activate intrinsic electric dipoles at the cellular level through numerical simulations. Third, this dissertation describes the use of MENs to track the neuronal activities in the brain (non-invasively) using a magnetic resonance and a magnetic nanoparticle imaging by monitoring the changes in the magnetization of the MENs surrounding the neuronal tissue under different states. The potential therapeutic and diagnostic impact of this innovative and novel study is highly significant not only in HIV-AIDS, Cancer, Parkinson’s and Alzheimer’s disease but also in many CNS and other diseases, where the ability to remotely control targeted drug delivery/release, and diagnostics is the key.

Impedance spectroscopy (IS) is an important tool for cell detection and characterization in medical and food safety applications. In this thesis, the Cal Poly Biofluidics Lab’s impedance spectroscopy system was re-evaluated and optimized for single-cell impedance spectroscopy. To evaluate the IS system, an impedance spectroscopy bioMEMS chip was fabricated in the Cal Poly Microfabcrication lab, software was developed to run IS experiments, and studies were run to validate the system. To explore IS optimization, Maxwell’s mixture theorem and the Schwartz-Christoffel transform were used to calculate an analytic impedance solution to the co-planar electrode system,a novel volume fraction to account for the non-uniformity of the electric field was developed to increase the accuracy of the analytic solution and to investigate the effect of cell position on the impedance spectrum, a software program was created to allow easy access to the analytic solution, and FEA models were developed to compare to the analytic solution and to investigate the effect of complex device geometry.

Blood flow velocity is an important parameter that can give information on several pathologies including atherosclerosis, glaucoma, Raynaud’s phenomenon, and ischemic stroke [2,5,6,10]. Present techniques of measuring blood flow velocity involve expensive procedures such as Doppler echocardiography, Doppler ultrasound, and magnetic resonance imaging [11,12]. They cost from $8500-$20000. It is desired to find a low-cost yet equally effective solution for measuring blood flow velocity. This thesis has a goal of creating a proof of concept device for measuring blood flow velocity. Finger blood flow velocity is investigated in this project. The close proximity to the skin of the finger’s arteries makes it a practical selection. A Red Green Blue (RGB) color sensor is integrated with an Arduino Uno microcontroller to analyze color on skin. The initial analysis involved utilization of red RGB values to measure heart rate; this was performed to validate the sensor. This test achieved similar results to an experimental control as the measurements had error ranging from 0% to 6.67%. The main analysis was to measure blood flow velocity using 2 RGB color sensors. The range of velocity found was 5.20cm/s to 12.22cm/s with an average of 7.44cm/s. This compared well with the ranges found in published data that varied from 4cm/s to 19cm/s. However, there is an error associated with the device that affects the accuracy of the results. The apparatus has the limitation of collecting data between sensors every 102-107ms, so there is a maximum error of 107ms. The average finger blood flow velocity of 7.44cm/s may actually be between 6.17cm/s and 9.39cm/s due to the sampling error. In addition, mean squared error analysis found that the most likely time difference between pulses among those found is 739ms, which corresponds to 5.21cm/s. Although there is error in the system, the tests for heart rate along with the obtained range and average for finger blood velocity data provided a method for analyzing blood flow velocity. Finger blood velocity was examined in a much more economical manner than its traditional methods that cost between $8500-$20000. The cost for this entire thesis was $99.66, which is a maximum of 1.17% of the cost.

The digenetic trematode, Bolbophorus damnificus, poses a substantial threat to catfish aquaculture, causing significant economic losses. Infestations lead to suppressed feed consumption, secondary bacterial infections and poor production performance. Survey data reveals widespread infestation in the in the southeastern United States. Current control strategies involve the application of a concentrated copper sulfate solution to reduce snail populations which serve as the first intermediate host of the trematode life cycle. This study aimed to improve treatment efficacy by developing a granular copper sulfate application system. A modified Gandy fertilizer applicator, equipped with a programmable control system, demonstrated accurate distribution of copper sulfate crystals along pond margins at various speeds. Granular copper sulfate was effective in killing snails along the pond margins at treatment rates between 1-3 ppm. The innovative system offers a practical, single-pass solution to combat trematode infestations in catfish ponds and minimizes logistical challenges associated with multiple applications.

Parkinson’s disease and Essential tremor are the two most prevalent movement disorders in the world, but due to overlapping clinical symptoms, accurate differential diagnosis is difficult. As a result, approximately 60% of patients with movement disorders symptoms will have their diagnosis changed at least once before death. By their subjective nature, clinical exams are inherently imprecise, leading to the desire to create an objective, quantifiable test for movement disorders; a test that currently is elusive. Eye movements have been studied for a century, and are widely appreciated to be quantifiably affected in those with neurological disease. Through a collaborative effort between the VA hospital and VCU, over 1,000 movement disorder subjects had their eye movements recorded, utilizing an SR Research Eyelink 2. Patients with Parkinson’s disease exhibited an ocular gaze tremor during fixation, normal reflexive saccades, and reduced blink rate. Subjects with Essential tremor exhibited slowed saccadic dynamics, with increased latencies, in addition to a larger number of square wave jerk interruptions of otherwise stable fixation. After diagnostic features of each disorder were identified, prospective data collection could occur in a blinded fashion, and oculomotor features used to predict clinical diagnoses. It was determined that measures of fixation stability were capable of almost perfectly differentiating subjects with PD, and a novel, combined parameter was capable of similar results in ET. As a group, it appears as if these symptoms do not progress as the disease does, but subanalyses show that individual patients on constant pharmaceutical doses tracked over time do slightly change and progress. The near perfect separation of disease states suggest the ability of oculomotor recording to be a powerful biomarker to be used for the differential diagnosis of movement disorders. This tool could potentially impact and improve the lives of millions of people the world over.