Matching Items (418)
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Description
A cerebral aneurysm is a bulging of a blood vessel in the brain. Aneurysmal rupture affects 25,000 people each year and is associated with a 45% mortality rate. Therefore, it is critically important to treat cerebral aneurysms effectively before they rupture. Endovascular coiling is the most effective treatment for cerebral

A cerebral aneurysm is a bulging of a blood vessel in the brain. Aneurysmal rupture affects 25,000 people each year and is associated with a 45% mortality rate. Therefore, it is critically important to treat cerebral aneurysms effectively before they rupture. Endovascular coiling is the most effective treatment for cerebral aneurysms. During coiling process, series of metallic coils are deployed into the aneurysmal sack with the intent of reaching a sufficient packing density (PD). Coils packing can facilitate thrombus formation and help seal off the aneurysm from circulation over time. While coiling is effective, high rates of treatment failure have been associated with basilar tip aneurysms (BTAs). Treatment failure may be related to geometrical features of the aneurysm. The purpose of this study was to investigate the influence of dome size, parent vessel (PV) angle, and PD on post-treatment aneurysmal hemodynamics using both computational fluid dynamics (CFD) and particle image velocimetry (PIV). Flows in four idealized BTA models with a combination of dome sizes and two different PV angles were simulated using CFD and then validated against PIV data. Percent reductions in post-treatment aneurysmal velocity and cross-neck (CN) flow as well as percent coverage of low wall shear stress (WSS) area were analyzed. In all models, aneurysmal velocity and CN flow decreased after coiling, while low WSS area increased. However, with increasing PD, further reductions were observed in aneurysmal velocity and CN flow, but minimal changes were observed in low WSS area. Overall, coil PD had the greatest impact while dome size has greater impact than PV angle on aneurysmal hemodynamics. These findings lead to a conclusion that combinations of treatment goals and geometric factor may play key roles in coil embolization treatment outcomes, and support that different treatment timing may be a critical factor in treatment optimization.
ContributorsIndahlastari, Aprinda (Author) / Frakes, David (Thesis advisor) / Chong, Brian (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Electromyogram (EMG)-based control interfaces are increasingly used in robot teleoperation, prosthetic devices control and also in controlling robotic exoskeletons. Over the last two decades researchers have come up with a plethora of decoding functions to map myoelectric signals to robot motions. However, this requires a lot of training and validation

Electromyogram (EMG)-based control interfaces are increasingly used in robot teleoperation, prosthetic devices control and also in controlling robotic exoskeletons. Over the last two decades researchers have come up with a plethora of decoding functions to map myoelectric signals to robot motions. However, this requires a lot of training and validation data sets, while the parameters of the decoding function are specific for each subject. In this thesis we propose a new methodology that doesn't require training and is not user-specific. The main idea is to supplement the decoding functional error with the human ability to learn inverse model of an arbitrary mapping function. We have shown that the subjects gradually learned the control strategy and their learning rates improved. We also worked on identifying an optimized control scheme that would be even more effective and easy to learn for the subjects. Optimization was done by taking into account that muscles act in synergies while performing a motion task. The low-dimensional representation of the neural activity was used to control a two-dimensional task. Results showed that in the case of reduced dimensionality mapping, the subjects were able to learn to control the device in a slower pace, however they were able to reach and retain the same level of controllability. To summarize, we were able to build an EMG-based controller for robot devices that would work for any subject, without any training or decoding function, suggesting human-embedded controllers for robotic devices.
ContributorsAntuvan, Chris Wilson (Author) / Artemiadis, Panagiotis (Thesis advisor) / Muthuswamy, Jitendran (Committee member) / Santos, Veronica J (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Gene manipulation techniques, such as RNA interference (RNAi), offer a powerful method for elucidating gene function and discovery of novel therapeutic targets in a high-throughput fashion. In addition, RNAi is rapidly being adopted for treatment of neurological disorders, such as Alzheimer's disease (AD), Parkinson's disease, etc. However, a major challenge

Gene manipulation techniques, such as RNA interference (RNAi), offer a powerful method for elucidating gene function and discovery of novel therapeutic targets in a high-throughput fashion. In addition, RNAi is rapidly being adopted for treatment of neurological disorders, such as Alzheimer's disease (AD), Parkinson's disease, etc. However, a major challenge in both of the aforementioned applications is the efficient delivery of siRNA molecules, plasmids or transcription factors to primary cells such as neurons. A majority of the current non-viral techniques, including chemical transfection, bulk electroporation and sonoporation fail to deliver with adequate efficiencies and the required spatial and temporal control. In this study, a novel optically transparent biochip is presented that can (a) transfect populations of primary and secondary cells in 2D culture (b) readily scale to realize high-throughput transfections using microscale electroporation and (c) transfect targeted cells in culture with spatial and temporal control. In this study, delivery of genetic payloads of different sizes and molecular characteristics, such as GFP plasmids and siRNA molecules, to precisely targeted locations in primary hippocampal and HeLa cell cultures is demonstrated. In addition to spatio-temporally controlled transfection, the biochip also allowed simultaneous assessment of a) electrical activity of neurons, b) specific proteins using fluorescent immunohistochemistry, and c) sub-cellular structures. Functional silencing of GAPDH in HeLa cells using siRNA demonstrated a 52% reduction in the GAPDH levels. In situ assessment of actin filaments post electroporation indicated a sustained disruption in actin filaments in electroporated cells for up to two hours. Assessment of neural spike activity pre- and post-electroporation indicated a varying response to electroporation. The microarray based nature of the biochip enables multiple independent experiments on the same culture, thereby decreasing culture-to-culture variability, increasing experimental throughput and allowing cell-cell interaction studies. Further development of this technology will provide a cost-effective platform for performing high-throughput genetic screens.
ContributorsPatel, Chetan (Author) / Muthuswamy, Jitendran (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Jain, Tilak (Committee member) / Caplan, Michael (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The use of electromyography (EMG) signals to characterize muscle fatigue has been widely accepted. Initial work on characterizing muscle fatigue during isometric contractions demonstrated that its frequency decreases while its amplitude increases with the onset of fatigue. More recent work concentrated on developing techniques to characterize dynamic contractions for use

The use of electromyography (EMG) signals to characterize muscle fatigue has been widely accepted. Initial work on characterizing muscle fatigue during isometric contractions demonstrated that its frequency decreases while its amplitude increases with the onset of fatigue. More recent work concentrated on developing techniques to characterize dynamic contractions for use in clinical and training applications. Studies demonstrated that as fatigue progresses, the EMG signal undergoes a shift in frequency, and different physiological mechanisms on the possible cause of the shift were considered. Time-frequency processing, using the Wigner distribution or spectrogram, is one of the techniques used to estimate the instantaneous mean frequency and instantaneous median frequency of the EMG signal using a variety of techniques. However, these time-frequency methods suffer either from cross-term interference when processing signals with multiple components or time-frequency resolution due to the use of windowing. This study proposes the use of the matching pursuit decomposition (MPD) with a Gaussian dictionary to process EMG signals produced during both isometric and dynamic contractions. In particular, the MPD obtains unique time-frequency features that represent the EMG signal time-frequency dependence without suffering from cross-terms or loss in time-frequency resolution. As the MPD does not depend on an analysis window like the spectrogram, it is more robust in applying the timefrequency features to identify the spectral time-variation of the EGM signal.
ContributorsAustin, Hiroko (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Kovvali, Narayan (Committee member) / Muthuswamy, Jitendran (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Advances in implantable MEMS technology has made possible adaptive micro-robotic implants that can track and record from single neurons in the brain. Development of autonomous neural interfaces opens up exciting possibilities of micro-robots performing standard electrophysiological techniques that would previously take researchers several hundred hours to train and achieve the

Advances in implantable MEMS technology has made possible adaptive micro-robotic implants that can track and record from single neurons in the brain. Development of autonomous neural interfaces opens up exciting possibilities of micro-robots performing standard electrophysiological techniques that would previously take researchers several hundred hours to train and achieve the desired skill level. It would result in more reliable and adaptive neural interfaces that could record optimal neural activity 24/7 with high fidelity signals, high yield and increased throughput. The main contribution here is validating adaptive strategies to overcome challenges in autonomous navigation of microelectrodes inside the brain. The following issues pose significant challenges as brain tissue is both functionally and structurally dynamic: a) time varying mechanical properties of the brain tissue-microelectrode interface due to the hyperelastic, viscoelastic nature of brain tissue b) non-stationarities in the neural signal caused by mechanical and physiological events in the interface and c) the lack of visual feedback of microelectrode position in brain tissue. A closed loop control algorithm is proposed here for autonomous navigation of microelectrodes in brain tissue while optimizing the signal-to-noise ratio of multi-unit neural recordings. The algorithm incorporates a quantitative understanding of constitutive mechanical properties of soft viscoelastic tissue like the brain and is guided by models that predict stresses developed in brain tissue during movement of the microelectrode. An optimal movement strategy is developed that achieves precise positioning of microelectrodes in the brain by minimizing the stresses developed in the surrounding tissue during navigation and maximizing the speed of movement. Results of testing the closed-loop control paradigm in short-term rodent experiments validated that it was possible to achieve a consistently high quality SNR throughout the duration of the experiment. At the systems level, new generation of MEMS actuators for movable microelectrode array are characterized and the MEMS device operation parameters are optimized for improved performance and reliability. Further, recommendations for packaging to minimize the form factor of the implant; design of device mounting and implantation techniques of MEMS microelectrode array to enhance the longevity of the implant are also included in a top-down approach to achieve a reliable brain interface.
ContributorsAnand, Sindhu (Author) / Muthuswamy, Jitendran (Thesis advisor) / Tillery, Stephen H (Committee member) / Buneo, Christopher (Committee member) / Abbas, James (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The basal ganglia are four sub-cortical nuclei associated with motor control and reward learning. They are part of numerous larger mostly segregated loops where the basal ganglia receive inputs from specific regions of cortex. Converging on these inputs are dopaminergic neurons that alter their firing based on received and/or predicted

The basal ganglia are four sub-cortical nuclei associated with motor control and reward learning. They are part of numerous larger mostly segregated loops where the basal ganglia receive inputs from specific regions of cortex. Converging on these inputs are dopaminergic neurons that alter their firing based on received and/or predicted rewarding outcomes of a behavior. The basal ganglia's output feeds through the thalamus back to the areas of the cortex where the loop originated. Understanding the dynamic interactions between the various parts of these loops is critical to understanding the basal ganglia's role in motor control and reward based learning. This work developed several experimental techniques that can be applied to further study basal ganglia function. The first technique used micro-volume injections of low concentration muscimol to decrease the firing rates of recorded neurons in a limited area of cortex in rats. Afterwards, an artificial cerebrospinal fluid flush was injected to rapidly eliminate the muscimol's effects. This technique was able to contain the effects of muscimol to approximately a 1 mm radius volume and limited the duration of the drug effect to less than one hour. This technique could be used to temporarily perturb a small portion of the loops involving the basal ganglia and then observe how these effects propagate in other connected regions. The second part applied self-organizing maps (SOM) to find temporal patterns in neural firing rate that are independent of behavior. The distribution of detected patterns frequency on these maps can then be used to determine if changes in neural activity are occurring over time. The final technique focused on the role of the basal ganglia in reward learning. A new conditioning technique was created to increase the occurrence of selected patterns of neural activity without utilizing any external reward or behavior. A pattern of neural activity in the cortex of rats was selected using an SOM. The pattern was then reinforced by being paired with electrical stimulation of the medial forebrain bundle triggering dopamine release in the basal ganglia. Ultimately, this technique proved unsuccessful possibly due to poor selection of the patterns being reinforced.
ContributorsBaldwin, Nathan Aaron (Author) / Helms Tillery, Stephen I (Thesis advisor) / Castaneda, Edward (Committee member) / Buneo, Christopher A (Committee member) / Muthuswamy, Jitendran (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2014
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Description
A noninvasive optical method is developed to monitor rapid changes in blood glucose levels in diabetic patients. The system depends on an optical cell built with a LED that emits light of wavelength 535nm that is a peak absorbance of hemoglobin. As the glucose concentration in the blood decreases, its

A noninvasive optical method is developed to monitor rapid changes in blood glucose levels in diabetic patients. The system depends on an optical cell built with a LED that emits light of wavelength 535nm that is a peak absorbance of hemoglobin. As the glucose concentration in the blood decreases, its osmolarity also decreases and the RBCs swell and decrease the path length absorption coefficient. Decreasing absorption coefficient increases the transmission of light through the whole blood. The system was tested with a constructed optical cell that held whole blood in a capillary tube. As expected the light transmitted to the photodiode increases with decreasing glucose concentration. The average response time of the system was between 30-40 seconds. The changes in size of the RBC cells in response to glucose concentration changes were confirmed using a cell counter and also visually under microscope. This method does not allow measuring the glucose concentration with an absolute concentration calibration. It is directed towards development of a device to monitor the changes in glucose concentration as an aid to diabetic management. This method might be improvised for precision and resolution and be developed as a ring or an earring that patients can wear.
ContributorsRajan, Shiny Amala Priya (Author) / Towe, Bruce (Thesis advisor) / Muthuswamy, Jitendran (Committee member) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The football helmet is a device used to help mitigate the occurrence of impact-related traumatic (TBI) and minor traumatic brain injuries (mTBI) in the game of American football. The current design methodology of using a hard shell with an energy absorbing liner may be adequate for minimizing TBI, however it

The football helmet is a device used to help mitigate the occurrence of impact-related traumatic (TBI) and minor traumatic brain injuries (mTBI) in the game of American football. The current design methodology of using a hard shell with an energy absorbing liner may be adequate for minimizing TBI, however it has had less effect in minimizing mTBI. The latest research in brain injury mechanisms has established that the current design methodology has produced a helmet to reduce linear acceleration of the head. However, angular accelerations also have an adverse effect on the brain response, and must be investigated as a contributor of brain injury.

To help better understand how the football helmet design features effect the brain response during impact, this research develops a validated football helmet model and couples it with a full LS-DYNA human body model developed by the Global Human Body Modeling Consortium (v4.1.1). The human body model is a conglomeration of several validated models of different sections of the body. Of particular interest for this research is the Wayne State University Head Injury Model for modeling the brain. These human body models were validated using a combination of cadaveric and animal studies. In this study, the football helmet was validated by laboratory testing using drop tests on the crown of the helmet. By coupling the two models into one finite element model, the brain response to impact loads caused by helmet design features can be investigated. In the present research, LS-DYNA is used to study a helmet crown impact with a rigid steel plate so as to obtain the strain-rate, strain, and stress experienced in the corpus callosum, midbrain, and brain stem as these anatomical regions are areas of concern with respect to mTBI.
ContributorsDarling, Timothy (Author) / Rajan, Subramaniam D. (Thesis advisor) / Muthuswamy, Jitendran (Thesis advisor) / Oswald, Jay (Committee member) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2014
Description
Filtration for microfluidic sample-collection devices is desirable for sample selection, concentration, preprocessing, and downstream manipulation, but microfabricating the required sub-micrometer filtration structure is an elaborate process. This thesis presents a simple method to fabricate polydimethylsiloxane (PDMS) devices with an integrated membrane filter that will sample, lyse, and extract the DNA

Filtration for microfluidic sample-collection devices is desirable for sample selection, concentration, preprocessing, and downstream manipulation, but microfabricating the required sub-micrometer filtration structure is an elaborate process. This thesis presents a simple method to fabricate polydimethylsiloxane (PDMS) devices with an integrated membrane filter that will sample, lyse, and extract the DNA from microorganisms in aqueous environments. An off-the-shelf membrane filter disc was embedded in a PDMS layer and sequentially bound with other PDMS channel layers. No leakage was observed during filtration. This device was validated by concentrating a large amount of cyanobacterium Synechocystis in simulated sample water with consistent performance across devices. After accumulating sufficient biomass on the filter, a sequential electrochemical lysing process was performed by applying 5VDC across the filter. This device was further evaluated by delivering several samples of differing concentrations of cyanobacterium Synechocystis then quantifying the DNA using real-time PCR. Lastly, an environmental sample was run through the device and the amount of photosynthetic microorganisms present in the water was determined. The major breakthroughs in this design are low energy demand, cheap materials, simple design, straightforward fabrication, and robust performance, together enabling wide-utility of similar chip-based devices for field-deployable operations in environmental micro-biotechnology.
ContributorsLecluse, Aurelie (Author) / Meldrum, Deirdre (Thesis advisor) / Chao, Joseph (Thesis advisor) / Westerhoff, Paul (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Microelectrodes have been used as the neural interface to record brain's neural activities. Most of these electrodes are fixed positioned. Neural signal normally degrades over time due to the body immune response and brain micromotion that move the neurons away from the microelectrode. MEMS technology under SUMMiT VTM processes has

Microelectrodes have been used as the neural interface to record brain's neural activities. Most of these electrodes are fixed positioned. Neural signal normally degrades over time due to the body immune response and brain micromotion that move the neurons away from the microelectrode. MEMS technology under SUMMiT VTM processes has developed miniaturized version of moveable microelectrodes that have the ability to recover the neural signal degradation by searching new cluster of neurons. To move the MEMS microelectrode a combination of four voltage waveforms must be applied to four thermally actuated microactuators. Previous design has used OmneticTM interconnect to transfer the waveforms from the external signal generators to the MEMS device. Unfortunately, the mechanism to attach and detach the OmneticTM interconnect introduce mechanical stress into the brain tissue that often caused raptures in the blood vessel. The goal of this project is to create an integrated System-On-Package Signal Generator that can be implanted on the brain of a rodent. A wireless system and a microcontroller are integrated together with the signal generators. The integrated system can be used to generate a series of voltage waveforms that can be customized to drive an array of MEMS movable microelectrodes when a triggered signal is received wirelessly. 3D stacking technique has been used to develop this Integrated System. 3D stacks lead to several favorable factors, such as (a) reduction in the power consumption of the system, (b) reduction in the overall form-factor of the package, and (c) significant reduction the weight of the package. There are a few challenges that must be overcome in this project, such as a commercially available microcontroller normally have an output voltage of 3.3 V to 5.5 V; however, a voltage of 7 - 8V is required to move the MEMS movable microelectrodes. To acquire higher density neural recording, more number of microelectrodes are needed. In this project, SoP Signal Generator is design to drive independently 3 moveable microelectrodes. Therefore, 12 voltage waveform are required. . However, the use of 12 signal generators is not a workable option since the system will be significantly large. This brings us to the other challenge, the limiting size of the rodent brain. Due to this factor, the SoP Signal Generator has to be deisgned to be able to fit without causing much pressure to the rodent's brain. For the first challenge, which is the limited output voltage of 3.3V on the microcontroller, the RC555 timers are used as an amplifier in addition to generating the signals. Demultiplexers have been for the next challenge, which is the need of 24 waveforms to drive 3 electrodes. For each waveform, 1 demultiplexer is used, making a total of 4 demultiplexers used in the entire system, which is a significant improvement from using 12 signal generators. The last challenge can be approached using 3D system stacking technique as mentioned above. The research aims of this project can be described as follows: (1) the testing and realization of the system part, and the designing of the system in a PCB level, (2) implementing and testing the SoP Signal Generator with the MEMS movable microelectrodes, The final outcome of this project can be used not only for neural applications, but also for more general applications that requires customized signal generations and wireless data transmission.
ContributorsTee, Zikai (Author) / Muthuswamy, Jitendran (Thesis advisor) / Sutanto, Jemmy (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2012