Matching Items (14)
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- All Subjects: Biomedical Engineering
- Genre: Masters Thesis
- Creators: Honeycutt, Claire
- Creators: Greger, Bradley
- Member of: Theses and Dissertations
Description
Flow measurement has always been one of the most critical processes in many industrial and clinical applications. The dynamic behavior of flow helps to define the state of a process. An industrial example would be that in an aircraft, where the rate of airflow passing the aircraft is used to determine the speed of the plane. A clinical example would be that the flow of a patient's breath which could help determine the state of the patient's lungs. This project is focused on the flow-meter that are used for airflow measurement in human lungs. In order to do these measurements, resistive-type flow-meters are commonly used in respiratory measurement systems. This method consists of passing the respiratory flow through a fluid resistive component, while measuring the resulting pressure drop, which is linearly related to volumetric flow rate. These types of flow-meters typically have a low frequency response but are adequate for most applications, including spirometry and respiration monitoring. In the case of lung parameter estimation methods, such as the Quick Obstruction Method, it becomes important to have a higher frequency response in the flow-meter so that the high frequency components in the flow are measurable. The following three types of flow-meters were: a. Capillary type b. Screen Pneumotach type c. Square Edge orifice type To measure the frequency response, a sinusoidal flow is generated with a small speaker and passed through the flow-meter that is connected to a large, rigid container. True flow is proportional to the derivative of the pressure inside the container. True flow is then compared with the measured flow, which is proportional to the pressure drop across the flow-meter. In order to do the characterization, two LabVIEW data acquisition programs have been developed, one for transducer calibration, and another one that records flow and pressure data for frequency response testing of the flow-meter. In addition, a model that explains the behavior exhibited by the flow-meter has been proposed and simulated. This model contains a fluid resistor and inductor in series. The final step in this project was to approximate the frequency response data to the developed model expressed as a transfer function.
ContributorsHu, Jianchen (Author) / Macia, Narciso (Thesis advisor) / Pollat, Scott (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2013
Description
Optical Fibers coupled to laser light sources, and Light Emitting Diodes are the two classes of technologies used for optogenetic experiments. Arizona State University's Flexible Display Center fabricates novel flexible Organic Light Emitting Diodes(OLEDs). These OLEDs have the capability of being monolithically fabricated over flexible, transparent plastic substrates and having power efficient ways of addressing high density arrays of LEDs. This thesis critically evaluates the technology by identifying the key advantages, current limitations and experimentally assessing the technology in in-vivo and in-vitro animal models. For in-vivo testing, the emitted light from a flat OLED panel was directly used to stimulate the neo-cortex in the M1 region of transgenic mice expressing ChR2 (B6.Cg-Tg (Thy1-ChR2/EYFP) 9Gfng/J). An alternative stimulation paradigm using a collimating optical system coupled with an optical fiber was used for stimulating neurons in layer 5 of the motor cortex in the same transgenic mice. EMG activity was recorded from the contralateral vastus lateralis muscles. In vitro testing of the OLEDs was done in primary cortical neurons in culture transfected with blue light sensitive ChR2. The neurons were cultured on a microelectrode array for taking neuronal recordings.
ContributorsShah, Ankur (Author) / Muthuswamy, Jitendran (Thesis advisor) / Greger, Bradley (Committee member) / Blain Christen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015
Description
Robust and stable decoding of neural signals is imperative for implementing a useful neuroprosthesis capable of carrying out dexterous tasks. A nonhuman primate (NHP) was trained to perform combined flexions of the thumb, index and middle fingers in addition to individual flexions and extensions of the same digits. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon action potential firing rates. The effect of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis, and Mutual Information Maximization was compared based on SVM classification performance. SVM classification was used to examine the functional parameters of (i) efficacy (ii) endurance to simulated failure and (iii) longevity of classification. The effect of using isolated-neuron and multi-unit firing rates was compared as the feature vector supplied to the SVM. The best classification performance was on post-implantation day 36, when using multi-unit firing rates the worst classification accuracy resulted from features selected with Wilcoxon signed-rank test (51.12 ± 0.65%) and the best classification accuracy resulted from Mutual Information Maximization (93.74 ± 0.32%). On this day when using single-unit firing rates, the classification accuracy from the Wilcoxon signed-rank test was 88.85 ± 0.61 % and Mutual Information Maximization was 95.60 ± 0.52% (degrees of freedom =10, level of chance =10%)
ContributorsPadmanaban, Subash (Author) / Greger, Bradley (Thesis advisor) / Santello, Marco (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2015
Description
Progressive gait disorder in Parkinson's disease (PD) is usually exhibited as reduced step/stride length and gait speed. People with PD also exhibit stooped posture, which can contribute to reduced step length and arm swing. Since gait and posture deficits in people with PD do not respond well to pharmaceutical and surgical treatments, novel rehabilitative therapies to alleviate these impairments are necessary. Many studies have confirmed that people with PD can improve their walking patterns when external cues are presented. Only a few studies have provided explicit real-time feedback on performance, but they did not report how well people with PD can follow the cues on a step-by-step basis. In a single-session study using a novel-treadmill based paradigm, our group had previously demonstrated that people with PD could follow step-length and back angle feedback and improve their gait and posture during treadmill walking. This study investigated whether a long-term (6-week, 3 sessions/week) real-time feedback training (RTFT) program can improve overground gait, upright posture, balance, and quality of life. Three subjects (mean age 70 ± 2 years) with mild to moderate PD (Hoehn and Yahr stage III or below) were enrolled and participated in the program. The RTFT sessions involved walking on a treadmill while following visual feedback of step length and posture (one at any given time) displayed on a monitor placed in front of the subject at eye-level. The target step length was set between 110-120% of the step length obtained during a baseline non-feedback walking trial and the target back angle was set at the maximum upright posture exhibited during a quiet standing task. Two subjects were found to significantly improve their posture and overground walking at post-training and these changes were retained six weeks after RTFT (follow-up) and the third subject improved his upright posture and gait rhythmicity. Furthermore, the magnitude of the improvements observed in these subjects was greater than the improvements observed in reports on other neuromotor interventions. These results provide preliminary evidence that real-time feedback training can be used as an effective rehabilitative strategy to improve gait and upright posture in people with PD.
ContributorsBaskaran, Deepika (Author) / Krishnamurthi, Narayanan (Thesis advisor) / Abbas, James (Thesis advisor) / Honeycutt, Claire (Committee member) / Arizona State University (Publisher)
Created2017
Description
Adapting to one novel condition of a motor task has been shown to generalize to other naïve conditions (i.e., motor generalization). In contrast, learning one task affects the proficiency of another task that is altogether different (i.e. motor transfer). Much more is known about motor generalization than about motor transfer, despite of decades of behavioral evidence. Moreover, motor generalization is studied as a probe to understanding how movements in any novel situations are affected by previous experiences. Thus, one could assume that mechanisms underlying transfer from trained to untrained tasks may be same as the ones known to be underlying motor generalization. However, the direct relationship between transfer and generalization has not yet been shown, thereby limiting the assumption that transfer and generalization rely on the same mechanisms. The purpose of this study was to test whether there is a relationship between motor generalization and motor transfer. To date, ten healthy young adult subjects were scored on their motor generalization ability and motor transfer ability on various upper extremity tasks. Although our current sample size is too small to clearly identify whether there is a relationship between generalization and transfer, Pearson product-moment correlation results and a priori power analysis suggest that a significant relationship will be observed with an increased sample size by 30%. If so, this would suggest that the mechanisms of transfer may be similar to those of motor generalization.
ContributorsSohani, Priyanka (Author) / Schaefer, Sydney (Thesis advisor) / Daliri, Ayoub (Committee member) / Honeycutt, Claire (Committee member) / Arizona State University (Publisher)
Created2018
Description
In medical imaging, a wide variety of methods are used to interrogate structural and physiological differences between soft tissues. One of the most ubiquitous methods in clinical practice is Magnetic Resonance Imaging (MRI), which has the advantage of limited invasiveness, soft tissue discrimination, and adequate volumetric resolution. A myriad of advanced MRI methods exists to investigate the microstructural, physiologic and metabolic characteristics of tissue. For example, Dynamic Contrast Enhanced (DCE) and Dynamic Susceptibility Contrast (DSC) MRI non-invasively interrogates the dynamic passage of an exogenously administered MRI contrast agent through tissue to quantify local tracer kinetic properties like blood flow, vascular permeability and tissue compartmental volume fractions. Recently, an improved understanding of the biophysical basis of DSC-MRI signals in brain tumors revealed a new approach to derive multiple quantitative biomarkers that identify intrinsic sub-voxel cellular and vascular microstructure that can be used differentiate tumor sub-types. One of these characteristic biomarkers called Transverse Relaxivity at Tracer Equilibrium (TRATE), utilizes a combination of DCE and DSC techniques to compute a steady-state metric which is particularly sensitive to cell size, density, and packing properties. This work seeks to investigate the sensitivity and potential utility of TRATE in a range of disease states including Glioblastomas, Amyotrophic Lateral Sclerosis (ALS), and Duchenne’s Muscular Dystrophy (DMD). The MRC measures of TRATE showed the most promise in mouse models of ALS where TRATE values decreased with disease progression, a finding that correlated with reductions in myofiber size and area, as quantified by immunohistochemistry. In the animal models of cancer and DMD, TRATE results were more inconclusive, due to marked heterogeneity across animals and treatment state. Overall, TRATE seems to be a promising new biomarker but still needs further methodological refinement due to its sensitivity to contrast to noise and further characterization owing to its non-specificity with respect to multiple cellular features (e.g. size, density, heterogeneity) that complicate interpretation.
ContributorsFuentes, Alberto (Author) / Quarles, Chad C (Thesis advisor) / Kodibagkar, Vikram (Thesis advisor) / Greger, Bradley (Committee member) / Arizona State University (Publisher)
Created2018
Description
Intracranial pressure is an important parameter to monitor, and elevated intracranial pressure can be life threatening. Elevated intracranial pressure is indicative of distress in the brain attributed by conditions such as aneurysm, traumatic brain injury, brain tumor, hydrocephalus, stroke, or meningitis.
Electrocorticography (ECoG) recordings are invaluable in understanding epilepsy and detecting seizure zones. However, ECoG electrodes cause a foreign body mass effect, swelling, and pneumocephaly, which results in elevation of intracranial pressure (ICP). Thus, the aim of this work is to design an intracranial pressure monitoring system that could augment ECoG electrodes.
A minimally invasive, low-cost epidural intracranial pressure monitoring system is developed for this purpose, using a commercial pressure transducer available for biomedical applications. The system is composed of a pressure transducer, sensing cup, electronics, and data acquisition system. The pressure transducer is a microelectromechanical system (MEMS)-based die that works on piezoresistive phenomenon with dielectric isolation for direct contact with fluids.
The developed system was bench tested and verified in an animal model to confirm the efficacy of the system for intracranial pressure monitoring. The system has a 0.1 mmHg accuracy and a 2% error for the 0-10 mmHg range, with resolution of 0.01 mmHg. This system serves as a minimally invasive (2 mm burr hole) epidural ICP monitor, which could augment existing ECoG electrode arrays, to simultaneously measure intracranial pressure along with the neural signals.
This device could also be employed with brain implants that causes elevation in ICP due to tissue - implant interaction often leading to edema. This research explores the concept and feasibility for integrating the sensing component directly on to the ECoG electrode arrays.
Electrocorticography (ECoG) recordings are invaluable in understanding epilepsy and detecting seizure zones. However, ECoG electrodes cause a foreign body mass effect, swelling, and pneumocephaly, which results in elevation of intracranial pressure (ICP). Thus, the aim of this work is to design an intracranial pressure monitoring system that could augment ECoG electrodes.
A minimally invasive, low-cost epidural intracranial pressure monitoring system is developed for this purpose, using a commercial pressure transducer available for biomedical applications. The system is composed of a pressure transducer, sensing cup, electronics, and data acquisition system. The pressure transducer is a microelectromechanical system (MEMS)-based die that works on piezoresistive phenomenon with dielectric isolation for direct contact with fluids.
The developed system was bench tested and verified in an animal model to confirm the efficacy of the system for intracranial pressure monitoring. The system has a 0.1 mmHg accuracy and a 2% error for the 0-10 mmHg range, with resolution of 0.01 mmHg. This system serves as a minimally invasive (2 mm burr hole) epidural ICP monitor, which could augment existing ECoG electrode arrays, to simultaneously measure intracranial pressure along with the neural signals.
This device could also be employed with brain implants that causes elevation in ICP due to tissue - implant interaction often leading to edema. This research explores the concept and feasibility for integrating the sensing component directly on to the ECoG electrode arrays.
ContributorsSampath Kumaran, Ranjani (Author) / Christen, Jennifer Blain (Thesis advisor) / Tillery, Stephen Helms (Committee member) / Greger, Bradley (Committee member) / Arizona State University (Publisher)
Created2015
Description
According to the CDC in 2010, there were 2.8 million emergency room visits costing $7.9 billion dollars for treatment of nonfatal falling injuries in emergency departments across the country. Falls are a recognized risk factor for unintentional injuries among older adults, accounting for a large proportion of fractures, emergency department visits, and urgent hospitalizations. The objective of this research was to identify and learn more about what factors affect balance using analysis techniques from nonlinear dynamics. Human balance and gait research traditionally uses linear or qualitative tests to assess and describe human motion; however, it is growing more apparent that human motion is neither a simple nor a linear task. In the 1990s Collins, first started applying stochastic processes to analyze human postural control system. Recently, Zakynthinaki et al. modeled human balance using the idea that humans will remain erect when perturbed until some boundary, or physical limit, is passed. This boundary is similar to the notion of basins of attraction in nonlinear dynamics and is referred to as the basin of stability. Human balance data was collected using dual force plates and Vicon marker position data for leans using only ankle movements and leans that were unrestricted. With this dataset, Zakynthinaki’s work was extended by comparing different algorithms used to create the critical curve (basin of stability boundary) that encloses the experimental data points as well as comparing the differences between the two leaning conditions.
ContributorsSmith, Victoria (Author) / Spano, Mark L (Thesis advisor) / Lockhart, Thurmon E (Thesis advisor) / Honeycutt, Claire (Committee member) / Arizona State University (Publisher)
Created2016
Description
Fall accident is a significant problem associated with our society both in terms of economic losses and human suffering [1]. In 2016, more than 800,000 people were hospitalized and over 33,000 deaths resulted from falling. Health costs associated with falling in 2016 yielded at 33% of total medical expenses in the US- mounting to approximately $31 billion per year. As such, it is imperative to find intervention strategies to mitigate deaths and injuries associated with fall accidents. In order for this goal to be realized, it is necessary to understand the mechanisms associated with fall accidents and more specifically, the movement profiles that may represent the cogent behavior of the locomotor system that may be amendable to rehabilitation and intervention strategies. In this light, this Thesis is focused on better understanding the factors influencing dynamic stability measure (as measured by Lyapunov exponents) during over-ground ambulation utilizing wireless Inertial Measurement Unit (IMU).
Four pilot studies were conducted: the First study was carried out to verify if IMU system was sophisticated enough to determine different load-carrying conditions. Second, to test the effects of walking inclinations, three incline levels on gait dynamic stability were examined. Third, tested whether different sections from the total gait cycle can be stitched together to assess LDS using the laboratory collected data. Finally, the fourth study examines the effect of “stitching” the data on dynamic stability measure from a longitudinally assessed (3-day continuous data collection) data to assess the effects of free-range data on assessment of dynamic stability.
Results indicated that load carrying significantly influenced dynamic stability measure but not for the floor inclination levels – indicating that future use of such measure should further implicate normalization of dynamic stability measures associated with different activities and terrain conditions. Additionally, stitching method was successful in obtaining dynamic stability measure utilizing free-living IMU data.
Four pilot studies were conducted: the First study was carried out to verify if IMU system was sophisticated enough to determine different load-carrying conditions. Second, to test the effects of walking inclinations, three incline levels on gait dynamic stability were examined. Third, tested whether different sections from the total gait cycle can be stitched together to assess LDS using the laboratory collected data. Finally, the fourth study examines the effect of “stitching” the data on dynamic stability measure from a longitudinally assessed (3-day continuous data collection) data to assess the effects of free-range data on assessment of dynamic stability.
Results indicated that load carrying significantly influenced dynamic stability measure but not for the floor inclination levels – indicating that future use of such measure should further implicate normalization of dynamic stability measures associated with different activities and terrain conditions. Additionally, stitching method was successful in obtaining dynamic stability measure utilizing free-living IMU data.
ContributorsMoon, Seong Hyun (Author) / Lockhart, Thurmon Eddy (Thesis advisor) / Lee, Hyunglae (Committee member) / Honeycutt, Claire (Committee member) / Arizona State University (Publisher)
Created2017
Description
Between 20%-30% of stroke survivors have foot drop. Foot drop is characterized by inadequate dorsiflexion required to clear the foot of the ground during the swing phase of gait, increasing the risk of stumbles and falls (Pouwels et al. 2009; Hartholt et al. 2011). External postural perturbations such as trips and slips are associated with high rate of falls in individuals with stroke (Forster et al. 1995). Falls often results in head, hip, and wrist injuries (Hedlund et al 1987; Parkkari et al. 1999). A critical response necessary to recover one’s balance and prevent a fall is the ability to evoke a compensatory step (Maki et al. 2003; Mansfield et al. 2013). This is the step taken to restore one’s balance and prevent a fall. However, this is difficult for stroke survivors with foot drop as normal gait is impaired and this translates to difficulty in evoking a compensatory step. To address both foot drop and poor compensatory stepping response, assistive devices such as the ankle-foot-orthosis (AFO) and functional electrical stimulator (FES) are generally prescribed to stroke survivors (Kluding et al. 2013; S. Whiteside et al. 2015). The use of these assistive devices improves walking speed, foot clearance, cadence, and step length of its users (Bethoux et al. 2014; Abe et al. 2009; Everaert et al. 2013; Alam et al. 2014). However, their impact on fall outcome in individuals with stroke in not well evaluated (Weerdesteyn et al. 2008). A recent study (Masood Nevisipour et al. 2019) where stroke survivors experienced a forward treadmill perturbation, mimicking a trip, reports that the impaired compensatory stepping response in stroke survivors in not due to the use of the assistive devices but to severe ankle impairments which these devices do not fully address. However, falls can also occur because of a slip. Slips constitute 40% of outdoor falls (Luukinen et al. 2000). In this study, results for fall rate and compensatory stepping response when subjects experience backward perturbations, mimicking slips, reveal that these devices do not impair the compensatory stepping response of its users.
ContributorsAnnan, Theophilus (Author) / Honeycutt, Claire (Thesis advisor) / Abbas, James (Committee member) / Peterson, Daniel (Committee member) / Arizona State University (Publisher)
Created2021