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Description
Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart of these algorithms is particle filtering (PF), a sequential Monte Carlo technique used to estimate the unknown parameters of dynamic systems. First, we analyze the bottlenecks in existing PF algorithms, and we propose a new parallel PF (PPF) algorithm based on the independent Metropolis-Hastings (IMH) algorithm. We show that the proposed PPF-IMH algorithm improves the root mean-squared error (RMSE) estimation performance, and we demonstrate that a parallel implementation of the algorithm results in significant reduction in inter-processor communication. We apply our implementation on a Xilinx Virtex-5 field programmable gate array (FPGA) platform to demonstrate that, for a one-dimensional problem, the PPF-IMH architecture with four processing elements and 1,000 particles can process input samples at 170 kHz by using less than 5% FPGA resources. We also apply the proposed PPF-IMH to waveform-agile sensing to achieve real-time tracking of dynamic targets with high RMSE tracking performance. We next integrate the PPF-IMH algorithm to track the dynamic parameters in neural sensing when the number of neural dipole sources is known. We analyze the computational complexity of a PF based method and propose the use of multiple particle filtering (MPF) to reduce the complexity. We demonstrate the improved performance of MPF using numerical simulations with both synthetic and real data. We also propose an FPGA implementation of the MPF algorithm and show that the implementation supports real-time tracking. For the more realistic scenario of automatically estimating an unknown number of time-varying neural dipole sources, we propose a new approach based on the probability hypothesis density filtering (PHDF) algorithm. The PHDF is implemented using particle filtering (PF-PHDF), and it is applied in a closed-loop to first estimate the number of dipole sources and then their corresponding amplitude, location and orientation parameters. We demonstrate the improved tracking performance of the proposed PF-PHDF algorithm and map it onto a Xilinx Virtex-5 FPGA platform to show its real-time implementation potential. Finally, we propose the use of sensor scheduling and compressive sensing techniques to reduce the number of active sensors, and thus overall power consumption, of electroencephalography (EEG) systems. We propose an efficient sensor scheduling algorithm which adaptively configures EEG sensors at each measurement time interval to reduce the number of sensors needed for accurate tracking. We combine the sensor scheduling method with PF-PHDF and implement the system on an FPGA platform to achieve real-time tracking. We also investigate the sparsity of EEG signals and integrate compressive sensing with PF to estimate neural activity. Simulation results show that both sensor scheduling and compressive sensing based methods achieve comparable tracking performance with significantly reduced number of sensors.
ContributorsMiao, Lifeng (Author) / Chakrabarti, Chaitali (Thesis advisor) / Papandreou-Suppappola, Antonia (Thesis advisor) / Zhang, Junshan (Committee member) / Bliss, Daniel (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2013
Description
This work focuses on a generalized assessment of source zone natural attenuation (SZNA) at chlorinated aliphatic hydrocarbon (CAH) impacted sites. Given the numbers of sites and technical challenges for cleanup there is a need for a SZNA method at CAH impacted sites. The method anticipates that decision makers will be interested in the following questions: 1-Is SZNA occurring and what processes contribute? 2-What are the current SZNA rates? 3-What are the longer-term implications? The approach is macroscopic and uses multiple lines-of-evidence. An in-depth application of the generalized non-site specific method over multiple site events, with sampling refinement approaches applied for improving SZNA estimates, at three CAH impacted sites is presented with a focus on discharge rates for four events over approximately three years (Site 1:2.9, 8.4, 4.9, 2.8kg/yr as PCE, Site 2:1.6, 2.2, 1.7, 1.1kg/y as PCE, Site 3:570, 590, 250, 240kg/y as TCE). When applying the generalized CAH-SZNA method, it is likely that different practitioners will not sample a site similarly, especially regarding sampling density on a groundwater transect. Calculation of SZNA rates is affected by contaminant spatial variability with reference to transect sampling intervals and density with variations in either resulting in different mass discharge estimates. The effects on discharge estimates from varied sampling densities and spacings were examined to develop heuristic sampling guidelines with practical site sampling densities; the guidelines aim to reduce the variability in discharge estimates due to different sampling approaches and to improve confidence in SZNA rates allowing decision-makers to place the rates in perspective and determine a course of action based on remedial goals. Finally bench scale testing was used to address longer term questions; specifically the nature and extent of source architecture. A rapid in-situ disturbance method was developed using a bench-scale apparatus. The approach allows for rapid identification of the presence of DNAPL using several common pilot scale technologies (ISCO, air-sparging, water-injection) and can identify relevant source architectural features (ganglia, pools, dissolved source). Understanding of source architecture and identification of DNAPL containing regions greatly enhances site conceptualization models, improving estimated time frames for SZNA, and possibly improving design of remedial systems.
ContributorsEkre, Ryan (Author) / Johnson, Paul Carr (Thesis advisor) / Rittmann, Bruce (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2013
Description
To further the efforts producing energy from more renewable sources, microbial electrochemical cells (MXCs) can utilize anode respiring bacteria (ARB) to couple the oxidation of an organic substrate to the delivery of electrons to the anode. Although ARB such as Geobacter and Shewanella have been well-studied in terms of their microbiology and electrochemistry, much is still unknown about the mechanism of electron transfer to the anode. To this end, this thesis seeks to elucidate the complexities of electron transfer existing in Geobacter sulfurreducens biofilms by employing Electrochemical Impedance Spectroscopy (EIS) as the tool of choice. Experiments measuring EIS resistances as a function of growth were used to uncover the potential gradients that emerge in biofilms as they grow and become thicker. While a better understanding of this model ARB is sought, electrochemical characterization of a halophile, Geoalkalibacter subterraneus (Glk. subterraneus), revealed that this organism can function as an ARB and produce seemingly high current densities while consuming different organic substrates, including acetate, butyrate, and glycerol. The importance of identifying and studying novel ARB for broader MXC applications was stressed in this thesis as a potential avenue for tackling some of human energy problems.
ContributorsAjulo, Oluyomi (Author) / Torres, Cesar (Thesis advisor) / Nielsen, David (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Popat, Sudeep (Committee member) / Arizona State University (Publisher)
Created2013
Description
Humans' ability to perform fine object and tool manipulation is a defining feature of their sensorimotor repertoire. How the central nervous system builds and maintains internal representations of such skilled hand-object interactions has attracted significant attention over the past three decades. Nevertheless, two major gaps exist: a) how digit positions and forces are coordinated during natural manipulation tasks, and b) what mechanisms underlie the formation and retention of internal representations of dexterous manipulation. This dissertation addresses these two questions through five experiments that are based on novel grip devices and experimental protocols. It was found that high-level representation of manipulation tasks can be learned in an effector-independent fashion. Specifically, when challenged by trial-to-trial variability in finger positions or using digits that were not previously engaged in learning the task, subjects could adjust finger forces to compensate for this variability, thus leading to consistent task performance. The results from a follow-up experiment conducted in a virtual reality environment indicate that haptic feedback is sufficient to implement the above coordination between digit position and forces. However, it was also found that the generalizability of a learned manipulation is limited across tasks. Specifically, when subjects learned to manipulate the same object across different contexts that require different motor output, interference was found at the time of switching contexts. Data from additional studies provide evidence for parallel learning processes, which are characterized by different rates of decay and learning. These experiments have provided important insight into the neural mechanisms underlying learning and control of object manipulation. The present findings have potential biomedical applications including brain-machine interfaces, rehabilitation of hand function, and prosthetics.
ContributorsFu, Qiushi (Author) / Santello, Marco (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Buneo, Christopher (Committee member) / Santos, Veronica (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2013
Description
Reaching movements are subject to noise in both the planning and execution phases of movement production. Although the effects of these noise sources in estimating and/or controlling endpoint position have been examined in many studies, the independent effects of limb configuration on endpoint variability have been largely ignored. The present study investigated the effects of arm configuration on the interaction between planning noise and execution noise. Subjects performed reaching movements to three targets located in a frontal plane. At the starting position, subjects matched one of two desired arm configuration 'templates' namely "adducted" and "abducted". These arm configurations were obtained by rotations along the shoulder-hand axis, thereby maintaining endpoint position. Visual feedback of the hand was varied from trial to trial, thereby increasing uncertainty in movement planning and execution. It was hypothesized that 1) pattern of endpoint variability would be dependent on arm configuration and 2) that these differences would be most apparent in conditions without visual feedback. It was found that there were differences in endpoint variability between arm configurations in both visual conditions, but these differences were much larger when visual feedback was withheld. The overall results suggest that patterns of endpoint variability are highly dependent on arm configuration, particularly in the absence of visual feedback. This suggests that in the presence of vision, movement planning in 3D space is performed using coordinates that are largely arm configuration independent (i.e. extrinsic coordinates). In contrast, in the absence of vision, movement planning in 3D space reflects a substantial contribution of intrinsic coordinates.
ContributorsLakshmi Narayanan, Kishor (Author) / Buneo, Christopher (Thesis advisor) / Santello, Marco (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis builds upon previous research exploring the different factors that influence divorce access attitudes, using data drawn from the General Social Survey in 1991, 1994, and 2008. I examine different social values and economic characteristics and their influence on divorce access attitudes, and explore gender differences within these factors. I examine how information drawn from this analysis supports the argument for Second Demographic Transition Theory as a theoretical framework to explain influential factors in the formation of divorce access attitudes. I conclude that social values variables related to attitudes towards sex behaviors remain significant predictors of divorce access attitudes. I also recognize that socioeconomic context bears influence on the formation of divorce access attitudes. Gender differences lead to the conclusion that behavior and interactions around divorce access attitude formation are dynamic and complex, but are effectively explained using Second Demographic Transition Theory.
ContributorsFrump, Jonathan (Author) / Hayford, Sarah (Thesis advisor) / Glick, Jennifer (Committee member) / Yabiku, Scott (Committee member) / Arizona State University (Publisher)
Created2013
Description
Image resolution limits the extent to which zooming enhances clarity, restricts the size digital photographs can be printed at, and, in the context of medical images, can prevent a diagnosis. Interpolation is the supplementing of known data with estimated values based on a function or model involving some or all of the known samples. The selection of the contributing data points and the specifics of how they are used to define the interpolated values influences how effectively the interpolation algorithm is able to estimate the underlying, continuous signal. The main contributions of this dissertation are three fold: 1) Reframing edge-directed interpolation of a single image as an intensity-based registration problem. 2) Providing an analytical framework for intensity-based registration using control grid constraints. 3) Quantitative assessment of the new, single-image enlargement algorithm based on analytical intensity-based registration. In addition to single image resizing, the new methods and analytical approaches were extended to address a wide range of applications including volumetric (multi-slice) image interpolation, video deinterlacing, motion detection, and atmospheric distortion correction. Overall, the new approaches generate results that more accurately reflect the underlying signals than less computationally demanding approaches and with lower processing requirements and fewer restrictions than methods with comparable accuracy.
ContributorsZwart, Christine M. (Author) / Frakes, David H (Thesis advisor) / Karam, Lina (Committee member) / Kodibagkar, Vikram (Committee member) / Spanias, Andreas (Committee member) / Towe, Bruce (Committee member) / Arizona State University (Publisher)
Created2013
Description
In situ remediation of contaminated aquifers, specifically in situ bioremediation (ISB), has gained popularity over pump-and-treat operations. It represents a more sustainable approach that can also achieve complete mineralization of contaminants in the subsurface. However, the subsurface reality is very complex, characterized by hydrodynamic groundwater movement, geological heterogeneity, and mass-transfer phenomena governing contaminant transport and bioavailability. These phenomena cannot be properly studied using commonly conducted laboratory batch microcosms lacking realistic representation of the processes named above. Instead, relevant processes are better understood by using flow-through systems (sediment columns). However, flow-through column studies are typically conducted without replicates. Due to additional sources of variability (e.g., flow rate variation between columns and over time), column studies are expected to be less reproducible than simple batch microcosms. This was assessed through a comprehensive statistical analysis of results from multiple batch and column studies. Anaerobic microbial biotransformations of trichloroethene and of perchlorate were chosen as case studies. Results revealed that no statistically significant differences were found between reproducibility of batch and column studies. It has further been recognized that laboratory studies cannot accurately reproduce many phenomena encountered in the field. To overcome this limitation, a down-hole diagnostic device (in situ microcosm array - ISMA) was developed, that enables the autonomous operation of replicate flow-through sediment columns in a realistic aquifer setting. Computer-aided design (CAD), rapid prototyping, and computer numerical control (CNC) machining were used to create a tubular device enabling practitioners to conduct conventional sediment column studies in situ. A case study where two remediation strategies, monitored natural attenuation and bioaugmentation with concomitant biostimulation, were evaluated in the laboratory and in situ at a perchlorate-contaminated site. Findings demonstrate the feasibility of evaluating anaerobic bioremediation in a moderately aerobic aquifer. They further highlight the possibility of mimicking in situ remediation strategies on the small-scale in situ. The ISMA is the first device offering autonomous in situ operation of conventional flow-through sediment microcosms and producing statistically significant data through the use of multiple replicates. With its sustainable approach to treatability testing and data gathering, the ISMA represents a versatile addition to the toolbox of scientists and engineers.
ContributorsMcClellan, Kristin (Author) / Halden, Rolf U. (Thesis advisor) / Johnson, Paul C (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2013
Description
The object of this study is to charac terize the effect of focused ultrasound stimulation (FUS) on the rat ce rvix which has been observed to speed its ripening during pregnancy. Ce rvical ripening is required for successful fetal delivery. Timed-pregnant Sprague-Dawley rats (n=36) were used. On day 14 of gestation, the FUS system was placed on the body surface of the rat over the cervix and ultrasound energy was applied to cervix for variable times up to 1 hour in the control group, the FUS system was placed on rats but no energy was applied. Daily measurement of cervix light-induced florescence (LIF, photon counts of collagen x-bridge fluorescence) were made on days 16 of gestation and daily until spont-aneous delivery (day22) to estimate changes in cervical ripening. We found that pulses of 680 KHz ultrasound at 25 Hertz, 1 millisecond pulse duration at 1W/cm^2 applied for as little as 30 minutes would immediately afterwards show the cervix to hav e ripened to the degree seen just before delivery on day 22. Delivery times, fetal weights and viability were unaffected in the FUS-treated animals.
ContributorsLuo, Daishen (Author) / Towe, Bruce C (Thesis advisor) / Wang, Xiao (Committee member) / Caplan, Michael (Committee member) / Arizona State University (Publisher)
Created2012
Description
Biofuel from microbial biomass is a viable alternative to current energy production practices that could mitigate greenhouse gas levels and reduce dependency on fossil fuels. Sustainable production of microbial biomass requires efficient utilization of nutrients like phosphorus (P). P is a limited resource which is vital for global food security. This paper seeks to understand the fate of P through biofuel production and proposes a proof-of-concept process to recover P from microbial biomass. The photosynthetic cyanobacterium Synechocystis sp. PCC 6803 is found to contain 1.4% P by dry weight. After the crude lipids are extracted for biofuel processing, 92% of the intercellular P is found within the residual biomass. Most intercellular P is associated with nucleic acids which remain within the cell after lipids are extracted. Phospholipids comprise a small percentage of cellular P. A wet chemical advanced oxidation process of adding 30% hydrogen peroxide followed by 10 min of microwave heating converts 92% of the total cellular P from organic-P and polyphosphate into orthophosphate. P was then isolated and concentrated from the complex digested matrix by use of resins. An anion exchange resin impregnated with iron nanoparticles demonstrates high affinity for P by sorbing 98% of the influent P through 20 bed volumes, but only was able to release 23% of it when regenerated. A strong base anion exchange resin sorbed 87% of the influent P through 20 bed volumes then released 50% of it upon regeneration. The overall P recovery process was able to recover 48% of the starting intercellular P into a pure and concentrated nutrient solution available for reuse. Further optimization of elution could improve P recovery, but this provides a proof-of-concept for converting residual biomass after lipid extraction to a beneficial P source.
ContributorsGifford, James McKay (Author) / Westerhoff, Paul (Thesis advisor) / Rittmann, Bruce (Committee member) / Vannela, Ravindhar (Committee member) / Arizona State University (Publisher)
Created2012