Matching Items (12)
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- All Subjects: Biomechanics
- Creators: Harrington Bioengineering Program
- Resource Type: Text
Description
A cerebral aneurysm is an abnormal ballooning of the blood vessel wall in the brain that occurs in approximately 6% of the general population. When a cerebral aneurysm ruptures, the subsequent damage is lethal damage in nearly 50% of cases. Over the past decade, endovascular treatment has emerged as an effective treatment option for cerebral aneurysms that is far less invasive than conventional surgical options. Nonetheless, the rate of successful treatment is as low as 50% for certain types of aneurysms. Treatment success has been correlated with favorable post-treatment hemodynamics. However, current understanding of the effects of endovascular treatment parameters on post-treatment hemodynamics is limited. This limitation is due in part to current challenges in in vivo flow measurement techniques. Improved understanding of post-treatment hemodynamics can lead to more effective treatments. However, the effects of treatment on hemodynamics may be patient-specific and thus, accurate tools that can predict hemodynamics on a case by case basis are also required for improving outcomes.Accordingly, the main objectives of this work were 1) to develop computational tools for predicting post-treatment hemodynamics and 2) to build a foundation of understanding on the effects of controllable treatment parameters on cerebral aneurysm hemodynamics. Experimental flow measurement techniques, using particle image velocimetry, were first developed for acquiring flow data in cerebral aneurysm models treated with an endovascular device. The experimental data were then used to guide the development of novel computational tools, which consider the physical properties, design specifications, and deployment mechanics of endovascular devices to simulate post-treatment hemodynamics. The effects of different endovascular treatment parameters on cerebral aneurysm hemodynamics were then characterized under controlled conditions. Lastly, application of the computational tools for interventional planning was demonstrated through the evaluation of two patient cases.
ContributorsBabiker, M. Haithem (Author) / Frakes, David H (Thesis advisor) / Adrian, Ronald (Committee member) / Caplan, Michael (Committee member) / Chong, Brian (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2013
Description
The global population over the age of 60 is estimated to rise to 23% by 2050 only increase the prevalence of functional neurological disorders and stroke. Increase in cases of functional neurological disorders and strokes will place a greater burden on the healthcare industry, specifically physical therapy. Physical therapy is vital for a patient’s recovery of motor function which is time demanding and taxing on the physical therapist. Wearable robotics have been proven to improve functional outcomes in gait rehabilitation by providing controlled high dosage and high-intensity training. Accurate control strategies for assistive robotic exoskeletons are vital for repetitive high precisions assistance for cerebral plasticity to occur.
This thesis presents a preliminary determination and design of a control algorithm for an assistive ankle device developed by the ASU RISE Laboratory. The assistive ankle device functions by compressing a spring upon heel strike during gait, remaining compressed during mid-stance and then releasing upon initiation of heel-off. The relationship between surface electromyography and ground reactions forces were used for identification of user-initiated heel-off. The muscle activation of the tibialis anterior combined with the ground reaction forces of the heel pressure sensor generated potential features that will be utilized in the revised control algorithm for the assistive ankle device. Work on this project must proceed in order to test and validate the revised control algorithm to determine its accuracy and precision.
This thesis presents a preliminary determination and design of a control algorithm for an assistive ankle device developed by the ASU RISE Laboratory. The assistive ankle device functions by compressing a spring upon heel strike during gait, remaining compressed during mid-stance and then releasing upon initiation of heel-off. The relationship between surface electromyography and ground reactions forces were used for identification of user-initiated heel-off. The muscle activation of the tibialis anterior combined with the ground reaction forces of the heel pressure sensor generated potential features that will be utilized in the revised control algorithm for the assistive ankle device. Work on this project must proceed in order to test and validate the revised control algorithm to determine its accuracy and precision.
ContributorsGaytan-Jenkins, Daniel Rinaldo (Author) / Zhang, Wenlong (Thesis director) / Tyler, Jamie (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Diabetes mellitus is a disease characterized by many chronic and acute conditions. With the prevalence and cost quickly increasing, we seek to improve on the current standard of care and create a rapid, label free sensor for glycated albumin (GA) index using electrochemical impedance spectroscopy (EIS). The antibody, anti-HA, was fixed to gold electrodes and a sine wave of sweeping frequencies was induced with a range of HA, GA, and GA with HA concentrations. Each frequency in the impedance sweep was analyzed for highest response and R-squared value. The frequency with both factors optimized is specific for both the antibody-antigen binding interactions with HA and GA and was determined to be 1476 Hz and 1.18 Hz respectively in purified solutions. The correlation slope between the impedance response and concentration for albumin (0 \u2014 5400 mg/dL of albumin) was determined to be 72.28 ohm/ln(mg/dL) with an R-square value of 0.89 with a 2.27 lower limit of detection. The correlation slope between the impedance response and concentration for glycated albumin (0 \u2014 108 mg/dL) was determined to be -876.96 ohm/ln(mg/dL) with an R-squared value of 0.70 with a 0.92 mg/dL lower limit of detection (LLD). The above data confirms that EIS offers a new method of GA detection by providing unique correlation with albumin as well as glycated albumin. The unique frequency response of GA and HA allows for modulation of alternating current signals so that several other markers important in the management of diabetes could be measured with a single sensor. Future work will be necessary to establish multimarker sensing on one electrode.
ContributorsEusebio, Francis Ang (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
The purpose of this study, which was done in conjunction with the Arizona Heart Foundation, was to evaluate whether pyridoxine accelerates ulcer wound healing in diabetic patients with ulcers in the lower extremities. In this study, 100 mg of pyridoxine per day was given to patients in the experimental group (while they receive normal wound treatment) while patients in the control group received normal treatment of wounds without the pyridoxine. Over time, wound healing was evaluated by photographing and then measuring the size of patients' ulcer wounds on the photographs. Results from the experimental group were compared with those of the control group to evaluate the efficacy of the pyridoxine treatment. In addition, comparisons of the healing rates were made with respect to whether the patients smoked, had hypertension or hypotension, and the patients' body mass indexes. It has been found that there was no statistically significant difference in the mean healing rates between the control groups and experimental groups. In addition, it has been found that smoking, BMI and blood pressure did not have a statistically appreciable effect on the difference in mean healing rates between the control and experimental groups. This is evidence that pyridoxine did not have a statistically significant effect on wound healing rates.
ContributorsHaupt, Shawn Anthony (Author) / Caplan, Michael (Thesis director) / Pauken, Christine (Committee member) / Pagan, Pedro (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
Description
Currently, the management of diabetes mellitus (DM) involves the monitoring of only blood glucose using self-monitoring blood glucose devices (SMBGs) followed by taking interventional steps, if needed. To increase the amount of information that diabetics can have to base DM care decisions off of, the development of an insulin biosensor is explored. Such a biosensor incorporates electrochemical impedance spectroscopy (EIS) to ensure an extremely sensitive platform. Additionally, anti-insulin antibody was immobilized onto the surface of a gold disk working electrode to ensure a highly specific sensing platform as well. EIS measurements were completed with a 5mV sine wave that was swept through the frequency spectrum of 100 kHz to 1 Hz on concentrations of insulin ranging from 0 pM to 100 μM. The frequency at which the interaction between insulin and its antibody was optimized was determined by finding out at which frequency the R2 and slope of the impedance-concentration plot were best. This frequency, otherwise known as the optimal binding frequency, was determined to be 459 Hz. Three separate electrodes were developed and the impedance data for each concentration measured at 459 Hz was averaged and plotted against the LOG (pM insulin) to construct the calibration curve. The response was calculated to be 263.64 ohms/LOG(pM insulin) with an R2 value of 0.89. Additionally, the average RSD was determined to be 19.24% and the LLD was calculated to be 8.47 pM, which is well below the physiological normal range. These results highlight the potential success of developing commercial point-of-care insulin biosensors or multi-marker devices operating with integrated insulin detection.
ContributorsDecke, Zachary William (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Cook, Curtiss (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
Description
Diabetes is a growing epidemic in developing countries, specifically in rural Kenya. In addition to the high cost of glucose testing, many diabetics in Kenya do not understand the importance of testing their blood glucose, let alone the nature of the disease. This project addresses the insufficiency of educational materials regarding diabetes in rural Kenya. The resulting documents can easily be adjusted for use in other developing countries.
ContributorsBuchak, Jacqueline (Author) / Caplan, Michael (Thesis director) / Snyder, Jan (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
With dwindling water resources due to drought and other pressures, water utilities are seeking to tap into alternative water sources as a means to improve water sustainability. Reclaimed water consists of treated wastewater and is widely used for non-potable purposes, such as irrigation, both agricultural and recreational. However, the reclaimed water distribution system can be subject to substantial regrowth of microorganisms, including opportunistic pathogens, even following rigorous disinfection. Factors that can influence regrowth include temperature, organic carbon levels, disinfectant type, and the time transported (i.e., water age) in the system. One opportunistic pathogen (OP) that is critical to understanding microbial activity in both reclaimed and drinking water distribution systems is Acanthamoeba. In order to better understand the potential for this amoeba to proliferate in reclaimed water systems and influence other OPs, a simulated reclaimed water distribution system was studied. The objective of this study was to compare the prevalence of Acanthamoeba and one of its endosymbionts, Legionella, across varying assimilable organic carbon (AOC) levels, temperatures, disinfectants, and water ages in a simulated reclaimed water distribution system. The results of the study showed that cooler temperatures, larger water age, and chlorine conditions yielded the lowest detection of Acanthamoeba gene copies per mL or cm2 for bulk water and biofilm samples, respectively.
ContributorsDonaldson, Kandace (Author) / Ankeny, Casey (Thesis director) / Edwards, Marc (Committee member) / Pruden, Amy (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The effect of conflicting sensorimotor memories on optimal force strategies was explored. Subjects operated a virtual object controlled by a physical handle to complete a simple straight-line task. Perturbations applied to the handle induced a period of increased error in subject accuracy. After two blocks of 33 trials, perturbations switched direction, inducing increased error from the previous trials. Subjects returned after a 24-hour period to complete a similar protocol, but beginning with the second context and ending with the first. Interference from the first context on each day caused an increase in initial error for the second (P < 0.05). Following the rest period, subjects showed retention of the sensorimotor memory from the previous day through significantly decreased initial error (P = 3x10-6). However, subjects showed an increase in forces for each new context resulting from a sub-optimal motor strategy. Higher levels of total effort (P < 0.05) and a lack of separation between force values for opposing and non-opposing digits (P > 0.05) indicated a strategy that used more energy to complete the task, even when rates of learning appeared identical or improved. Two possible mechanisms for this lack of energy conservation have been proposed.
ContributorsSmith, Michael David (Author) / Santello, Marco (Thesis director) / Kleim, Jeffrey (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Carbohydrate counting has been shown to improve HbA1c levels for people with diabetes. However, the learning curve and inconvenience of carbohydrate counting make it difficult for patients to adhere to it. A deep learning model is proposed to identify food from an image, where it can help the user manage their carbohydrate counting. This early model has a 68.3% accuracy of identifying 101 different food classes. A more refined model in future work could be deployed into a mobile application to identify food the user is about to consume and log it for easier carbohydrate counting.
ContributorsCarreto, Cesar (Author) / Pizziconi, Vincent (Thesis director) / Vernon, Brent (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Medial compartment knee osteoarthritis (OA) is a disease whose severity has been associated with the peak adduction moment during walking (pKAM). Unfortunately, measuring patients' pKAM to track their therapy progress involves the use of a gait laboratory which is expensive and time intensive. This study aimed to develop and assess a regression method to predict the pKAM using only plantar pressure measurements. This approach could greatly reduce the burden of evaluating pKAM.
ContributorsThomas, Kevin Andrew (Author) / Hinrichs, Richard (Thesis director) / Harper, Erin (Committee member) / Favre, Julien (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05