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.

Multielectrode arrays may have several advantages compared to the traditional single macroelectrode brain electrical stimulation technique including less tissue damage due to implantation and the ability to deliver several spatio-temporal patterns of stimulation. Prior work on cell cultures has shown that multielectrode arrays are capable of completely stopping seizure-like spontaneous bursting events through a distributed asynchronous multi-site approach. In my studies, I used a similar approach for controlling seizures in a rat model of temporal lobe epilepsy. First, I developed a new method of electroplating in vivo microelectrode arrays for durably improving their impedance. I showed that microelectrode arrays electroplated through the new technique called sonicoplating, required the least amount of voltage in current controlled stimulation studies and also produced the least amplitude and duration of stimulation artifact compared to unplated, DC electroplated or pulse-plated microelectrodes. Second, using c-fos immunohistochemistry, I showed that 16-electrode sonicoplated microelectrode arrays can activate 5.9 times more neurons in the dorsal hippocampus compared to a single macroelectrodes while causing < 77% the tissue damage. Next, through open-loop multisite asynchronous microstimulation, I reduced seizure frequency by ~50% in the rodent model of temporal lobe epilepsy. Preliminary studies aimed at using the same stimulation protocol in closed-loop responsive and predictive seizure control did not stop seizures. Finally, through an internship at Medtronic Neuromodulation, I worked on developing and implementing a rapid algorithm prototyping research tool for closed-loop human deep brain stimulation applications.

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.

Normal movement execution requires proper coupling of motor and sensory activation. An increasing body of literature supports the idea that incorporation of sensory stimulation into motor rehabilitation practices increases its effectiveness. Paired associative stimulation (PAS) studies, in which afferent and efferent pathways are activated in tandem, have brought attention to the importance of well-timed stimulation rather than non-associative (i.e., open-loop) activation. In patients with tetraplegia resulting from spinal cord injury (SCI), varying degrees of upper limb function may remain and could be harnessed for rehabilitation. Incorporating associative sensory stimulation coupled with self-paced motor training would be a means for supplementing sensory deficits and improving functional outcomes. In a motor rehabilitation setting, it seems plausible that sensory feedback stimulation in response to volitional movement execution (to the extent possible), which is not utilized in most PAS protocols, would produce greater benefits. This capability is developed and tested in the present study by implementing a brain-computer interface (BCI) to apply sensory stimulation synchronized with movement execution through the detection of movement intent in real time from electroencephalography (EEG). The results demonstrate that accurate sensory stimulation application in response to movement intent is feasible in SCI patients with chronic motor deficit and often precedes the onset of movement, which is deemed optimal by PAS investigations that do not involve a volitional movement task.

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient’s extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.

Near infrared spectroscopy (NIRS) is an emerging non-invasive optical neuro imaging technique that monitors the hemodynamic response to brain activation with ms-scale temporal resolution and sub-cm spatial resolution. The overall goal of my dissertation was to develop and apply NIRS towards investigation of neurological response to language, joint attention and planning and execution of motor skills in healthy adults. Language studies were performed to investigate the hemodynamic response, synchrony and dominance feature of the frontal and fronto-temporal cortex of healthy adults in response to language reception and expression. The mathematical model developed based on granger causality explicated the directional flow of information during the processing of language stimuli by the fronto-temporal cortex. Joint attention and planning/ execution of motor skill studies were performed to investigate the hemodynamic response, synchrony and dominance feature of the frontal cortex of healthy adults and in children (5-8 years old) with autism (for joint attention studies) and individuals with cerebral palsy (for planning/execution of motor skills studies). The joint attention studies on healthy adults showed differences in activation as well as intensity and phase dependent connectivity in the frontal cortex during joint attention in comparison to rest. The joint attention studies on typically developing children showed differences in frontal cortical activation in comparison to that in children with autism. The planning and execution of motor skills studies on healthy adults and individuals with cerebral palsy (CP) showed difference in the frontal cortical dominance, that is, bilateral and ipsilateral dominance, respectively. The planning and execution of motor skills studies also demonstrated the plastic and learning behavior of brain wherein correlation was found between the relative change in total hemoglobin in the frontal cortex and the kinematics of the activity performed by the participants. Thus, during my dissertation the NIRS neuroimaging technique was successfully implemented to investigate the neurological response of language, joint attention and planning and execution of motor skills in healthy adults as well as preliminarily on children with autism and individuals with cerebral palsy. These NIRS studies have long-term potential for the design of early stage interventions in children with autism and customized rehabilitation in individuals with cerebral palsy.