Experimental Characterization of Vascular Tissue Viscoelasticity with Emphasis on Elastin's Role

Elucidating how cardiovascular biomechanics is regulated during health and disease is critical for developing diagnostic and therapeutic methods. The extracellular matrix of cardiovascular tissue is composed of multiple fibrillar networks embedded in an amorphous ground substance and has been found to reveal time-dependent mechanical behavior. Given the multiscale nature of tissue biomechanics, an accurate description of cardiovascular biomechanics can be obtained only when microstructural morphology is characterized and put together in correlation with tissue-scale mechanics. This study constitutes the initial steps toward a full description of cardiovascular tissue biomechanics by examining two fundamental questions: How does the elastin microstructure change with tissue-level deformations? And how does the extracellular matrix composition affect tissue biomechanics? The outcome of this dissertation is believed to contribute to the field of cardiovascular tissue biomechanics by addressing some of the fundamental existing questions therein. Assessing alterations in microstructural morphology requires quantified measures which can be challenging given the complex, local and interconnected conformations of tissue structural components embedded in the extracellular matrix. In this study, new image-based methods for quantification of tissue microstructure were developed and examined on aortic tissue under different deformation states. Although in their infancy stages of development, the methods yielded encouraging results consistent with existing perceptions of tissue deformation. Changes in microstructure were investigated by examining histological images of deformed and undeformed tissues. The observations shed light on roles of elastin network in regulating tissue deformation. The viscoelastic behavior of specimens was studied using native, collagen-denatured, and elastin-isolated aortic tissues. The stress-relaxation responses of specimens provide insight into the significance of extracellular matrix composition on tissue biomechanics and how the tissue hydration affects the relaxation behavior. The responses were approximated by traditional spring-dashpot models and the results were interpreted in regards to microstructural composition

Computational modeling of the brain limbic system and its application in control engineering

This study mainly deals with the various aspects of modeling the learning processes within the brain limbic system and studying the various aspects of using it for different applications in control engineering. The current study is a multi-aspect research effort which not only requires a background of control engineering, but also a basic knowledge of some biomorphic systems. The main focus of this study is on biological systems which are involved in emotional processes. In mammalians, a part of the brain called the limbic system is mainly responsible for emotional processes. Therefore, general brain emotional processes and specific aspects of the limbic system are reviewed in the early parts of this study. Next, we describe developing a computational model of the limbic system based on these concepts. Since the focus of this study is on the application of the model in engineering systems and not on the biological concepts, the model established is not a very complicated model and does not include all the components of the limbic system. In fact, we are trying to develop a model which captures the minimal and basic properties of the limbic system which are mainly known as the Amygdala-Orbitofrontal Cortex system. The main chapter of this thesis, Chapter IV, shows the utilization of the Brain Emotional Learning (BEL) model in different applications of control and signal fusion systems. The main effort is focused on applying the model to control systems where the model acts as the controller block. Furthermore, the application of the model in signal fusion is also considered where simulation results support the applicability of the model. Finally, we studied different analytical aspects of the model including the behavior of the system during the adaptation phase and the stability of the system. For the first issue, we simplify the model, e.g. remove the nonlinearities, to develop mathematical formulations for behavior of the system. To study the stability of the system, we use the cell-to-cell mapping algorithm which reveals the stability conditions of the system in different representations. This thesis finishes with some concluding remarks and some topics for future research on this field

A Multifaceted Device for Discreetly Acquiring Natural Behaviors of Children with Autism

Autism is a multifaceted neurological disorder that affects the four fundamental areas of sensory processing, communication mechanisms, social interaction skills, and whole child/self-esteem. The underlying mechanisms and symptoms of the disorder have been shown to largely vary from patient to patient, and therefore, a durable, effective therapy is best achieved through multifaceted, multidisciplinary approaches that allow a direct assessment of each individual’s behavior, both quantitatively and qualitatively. The aim of this project was to simulate, design, manufacture, and assess a device that can help cultivate sensory, social, communication, and motor skills in autistic children while being able to extract data of the child’s behavior that could be used by the therapist. Critical components of the toy involve auditory and visual stimulation, as well as interactive mechanisms to promote development. The most important features of the toy are hidden cameras that discreetly monitor the child’s reactions in order to provide analytical feedback mechanisms, allowing parents, caregivers, or therapists to monitor and evaluate the child’s learning and therapy. The performance of the toy was examined on 17 children with autism at two specialized centers for child with developmental disorders. The results showed that the device was found satisfactory by the majority of children as assessed by their willingness to spend time accomplishing the tasks on the device, as well as by captured videos of their natural reactions throughout. Furthermore, improved performance was observed on the same population of children who were tested multiple times, indicating the potential use of the toy for therapeutic and learning purposes

Detection of aortic wall inclusions using regional pulse wave propagation and velocity in silico

Abstract Monitoring of the regional stiffening of the arterial wall may prove important in the diagnosis of various vascular pathologies. The pulse wave velocity (PWV) along the aortic wall has been shown to be dependent on the wall stiffness and has played a fundamental role in a range of diagnostic methods. Conventional clinical methods entail global examination of the pulse traveling between two remote sites, e.g. femoral and carotid arteries, to provide an average PWV estimate. However, the majority of vascular diseases entail regional vascular changes and therefore may not be detected by a global PWV estimate. In this paper, a fluidstructure interaction study of straight-geometry aortas of 350 mm length is described aimed at examining the effects of regional stiffness changes on the PWV. Five homogeneous aortas with increasing wall stiffness as well as two aortas with soft and hard inclusions of 5 mm length were considered. In each case, spatio-temporal maps of the wall motion were used to analyze the regional pulse wave propagation. On the homogeneous aortas, increasing PWVs were found to increase with the wall moduli (R 2 Z0:9988), indicating the reliability of the model to accurately represent the wave propagation. On the inhomogeneous aortas, formation of reflected and standing waves was observed at the site of the hard and soft inclusions, respectively. Neither the hard nor the soft inclusion had a significant effect on the velocity of the traveling pulse beyond the inclusion site, which supported the hypothesis that a global measurement of the average PWV could fail to detect small, regional abnormalities

FSI Simulations of Pulse Wave Propagation in Human Abdominal Aortic Aneurysm: The Effects of Sac Geometry and Stiffness

This study aims to quantify the effects of geometry and stiffness of aneurysms on the pulse wave velocity (PWV) and propagation in fluid-solid interaction (FSI) simulations of arterial pulsatile flow. Spatiotemporal maps of both the wall displacement and fluid velocity were generated in order to obtain the pulse wave propagation through fluid and solid media, and to examine the interactions between the two waves. The results indicate that the presence of abdominal aortic aneurysm (AAA) sac and variations in the sac modulus affect the propagation of the pulse waves both qualitatively (eg, patterns of change of forward and reflective waves) and quantitatively (eg, decreasing of PWV within the sac and its increase beyond the sac as the sac stiffness increases). The sac region is particularly identified on the spatiotemporal maps with a region of disruption in the wave propagation with multiple short-traveling forward/reflected waves, which is caused by the change in boundary conditions within the saccular region. The change in sac stiffness, however, is more pronounced on the wall displacement spatiotemporal maps compared to those of fluid velocity. We conclude that the existence of the sac can be identified based on the solid and fluid pulse waves, while the sac properties can also be estimated. This study demonstrates the initial findings in numerical simulations of FSI dynamics during arterial pulsations that can be used as reference for experimental and in vivo studies. Future studies are needed to demonstrate the feasibility of the method in identifying very mild sacs, which cannot be detected from medical imaging, where the material property degradation exists under early disease initiation

On the multiscale modeling of heart valve biomechanics in health and disease

Theoretical models of the human heart valves are useful tools for understanding and characterizing the dynamics of healthy and diseased valves. Enabled by advances in numerical modeling and in a range of disciplines within experimental biomechanics, recent models of the heart valves have become increasingly comprehensive and accurate. In this paper, we first review the fundamentals of native heart valve physiology, composition and mechanics in health and disease. We will then furnish an overview of the development of theoretical and experimental methods in modeling heart valve biomechanics over the past three decades. Next, we will emphasize the necessity of using multiscale modeling approaches in order to provide a comprehensive description of heart valve biomechanics able to capture general heart valve behavior. Finally, we will offer an outlook for the future of valve multiscale modeling, the potential directions for further developments and the challenges involved

IMPLEMENTATION OF A GENETICALLY OPTIMIZED INTERPOLATIVE FUZZY INFERENCE ENGINE IN CONTROLLING A BALL-PLATE LABORATORY SETUP

ABSTRACT This paper goes through giving the results of implementing a genetically optimized interpolative fuzzy engine in controlling a ball-plate laboratory setup. For demonstrating the advantages of our proposed interpolative fuzzy controller over classical fuzzy controllers, we gave some comparison between the fuzzy controllers, one with common CRI inference mechanism and one with our interpolative inference mechanism. As expected, our fuzzy interpolative controller is more efficient than CRI-based controller, with respect to computational space, as well as it is more robust to goal achievement

Present address: Ultrasound and Elasticity Imaging Laboratory, Columbia University 630 W 168th St., Physicians and Surgeons 19-418

Abstract Arterial stiffness is a well-established biomarker for cardiovascular risk, especially in the case of hypertension. The progressive stages of an abdominal aortic aneurysm (AAA) have also been associated with varying arterial stiffness. Pulse wave imaging (PWI) is a noninvasive, ultrasound imagingbased technique that uses the pulse wave-induced arterial wall motion to map the propagation of the pulse wave and measure the regional pulse wave velocity (PWV) as an index of arterial stiffness. In this study, the clinical feasibility of PWI was evaluated in normal, hypertensive, and aneurysmal human aortas. Radiofrequency-based speckle tracking was used to estimate the pulse waveinduced displacements in the abdominal aortic walls of normal (N = 15, mean age 32.5 ± 10.2 years), hypertensive (N = 13, mean age 60.8 ± 15.8 years), and aneurysmal (N = 5, mean age 71.6 ± 11.8 years) human subjects. Linear regression of the spatio-temporal variation of the displacement waveform in the anterior aortic wall over a single cardiac cycle yielded the slope as the PWV and the coefficient of determination r 2 as an approximate measure of the pulse wave propagation uniformity. The aortic PWV measurements in all normal, hypertensive, and AAA subjects were 6.03 ± 1.68, 6.69 ± 2.80, and 10.54 ± 6.52 m s −1 , respectively. There was no significant difference (p = 0.15) between the PWVs of the normal and hypertensive subjects while the PWVs of the AAA subjects were significantly higher (p < 0.001) compared to those of the other two groups. Also, the average r 2 in the AAA subjects was significantly lower (p < 0.001) than that in the normal and hypertensive subjects. These preliminary results suggest that the regional PWV and the pulse wave propagation uniformity (r 2 ) obtained using PWI, in addition to the PWI images and spatio-temporal maps that provide qualitative visualization of