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Description
Basilisk lizards are often studied for their unique ability to run across the surface of

water. Due to the complicated fluid dynamics of this process, the forces applied on the

water’s surface cannot be measured using traditional methods. This thesis presents a

novel technique of measuring the forces using a fluid dynamic force

Basilisk lizards are often studied for their unique ability to run across the surface of

water. Due to the complicated fluid dynamics of this process, the forces applied on the

water’s surface cannot be measured using traditional methods. This thesis presents a

novel technique of measuring the forces using a fluid dynamic force platform (FDFP),

a light, rigid box immersed in water. This platform, along with a motion capture

system, can be used to characterize the kinematics and dynamics of a basilisk lizard

running on water. This could ultimately lead to robots that can run on water in a

similar manner.
ContributorsSweeney, Andrew Joseph (Author) / Marvi, Hamidreza (Thesis advisor) / Lentink, David (Committee member) / Lee, Hyunglae (Committee member) / Arizona State University (Publisher)
Created2019
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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

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.
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
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Description
Concept mapping is a tool used in order to visually represent a person's understanding of interrelated concepts. Generally the central concept is in the center or at the top and the related concepts branch off, becoming more detailed as it continues. Additionally, links between different branches show how those concepts

Concept mapping is a tool used in order to visually represent a person's understanding of interrelated concepts. Generally the central concept is in the center or at the top and the related concepts branch off, becoming more detailed as it continues. Additionally, links between different branches show how those concepts are related to each other. Concept mapping can be implemented in many different types of classrooms because it can be easily adjusted for the needs of the teacher and class specifically. The goal of this project is to analyze both the attitude and achievement of students using concept mapping of college students in an active learning classroom. In order to evaluate the students' concept maps we will use the expert map scoring method, which compares the students concept maps to an expertly created concept map for similarities; the more similar the two maps are, the higher the score. We will collect and record students' scores on concept maps as they continue through the one semester class. Certain chapters correspond to specific exams due to the information contained in the lectures, chapters 1-4 correspond to exam 1 and so forth. We will use this information to correlate the average concept map score across these chapters to one exam score. There was no significant correlation found between the exam grades and the corresponding scores on the concept maps (Pearson's R values of 0.27, 0.26, and -0.082 for Exam 1, 2 and 3 respectively). According to Holm et all "it was found that 85% of students found interest or attainment in the concept mapping session, only 44% thought there was a cost, and 63% thought it would help them to be successful."
ContributorsFarrell, Carilee Dawn (Author) / Ankeny, Casey (Thesis director) / Middleton, James (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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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

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
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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

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
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Description
This thesis work presents two separate studies:The first study assesses standing balance under various 2-dimensional (2D) compliant environments simulated using a dual-axis robotic platform and vision conditions. Directional virtual time-to-contact (VTC) measures were introduced to better characterize postural balance from both temporal and spatial aspects, and enable prediction of fall-relevant

This thesis work presents two separate studies:The first study assesses standing balance under various 2-dimensional (2D) compliant environments simulated using a dual-axis robotic platform and vision conditions. Directional virtual time-to-contact (VTC) measures were introduced to better characterize postural balance from both temporal and spatial aspects, and enable prediction of fall-relevant directions. Twenty healthy young adults were recruited to perform quiet standing tasks on the platform. Conventional stability measures, namely center-of-pressure (COP) path length and COP area, were also adopted for further comparisons with the proposed VTC. The results indicated that postural balance was adversely impacted, evidenced by significant decreases in VTC and increases in COP path length/area measures, as the ground compliance increased and/or in the absence of vision (ps < 0.001). Interaction effects between environment and vision were observed in VTC and COP path length measures (ps ≤ 0.05), but not COP area (p = 0.103). The estimated likelihood of falls in anterior-posterior (AP) and medio-lateral (ML) directions converged to nearly 50% (almost independent of the foot setting) as the experimental condition became significantly challenging. The second study introduces a deep learning approach using convolutional neural network (CNN) for predicting environments based on instant observations of sway during balance tasks. COP data were collected from fourteen subjects while standing on the 2D compliant environments. Different window sizes for data segmentation were examined to identify its minimal length for reliable prediction. Commonly-used machine learning models were also tested to compare their effectiveness with that of the presented CNN model. The CNN achieved above 94.5% in the overall prediction accuracy even with 2.5-second length data, which cannot be achieved by traditional machine learning models (ps < 0.05). Increasing data length beyond 2.5 seconds slightly improved the accuracy of CNN but substantially increased training time (60% longer). Importantly, averaged normalized confusion matrices revealed that CNN is much more capable of differentiating the mid-level environmental condition. These two studies provide new perspectives in human postural balance, which cannot be interpreted by conventional stability analyses. Outcomes of these studies contribute to the advancement of human interactive robots/devices for fall prevention and rehabilitation.
ContributorsPhan, Vu Nguyen (Author) / Lee, Hyunglae (Thesis advisor) / Peterson, Daniel (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Human walking is a complex and rhythmical activity that comprises of the brain, nerves and muscles. Neuromuscular disorder (NMD) is a broad term that refers to conditions that affect the proper use of muscles and nervous system, thus also impairing the walking or gait cycle of an individual. The improper

Human walking is a complex and rhythmical activity that comprises of the brain, nerves and muscles. Neuromuscular disorder (NMD) is a broad term that refers to conditions that affect the proper use of muscles and nervous system, thus also impairing the walking or gait cycle of an individual. The improper gait cycle might be attributed to the lack of force produced at the toe-off stage. This project addresses if it is possible to create an OpenSim model to find the ideal time and force magnitude needed of an assistive force ankle device to improve gait patterns in individuals with NMD.
ContributorsRivera, Jose Luis (Author) / Zhang, Wenlong (Thesis director) / Lockhart, Thurmon (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Over the past 30 years the use of graphene has been increasing at a rapid rate. The reason why graphene has become more popular is because it is starting to be understood better, and researchers are starting to recognize graphene’s unique properties. Graphene is a single atomic layer of graphite,

Over the past 30 years the use of graphene has been increasing at a rapid rate. The reason why graphene has become more popular is because it is starting to be understood better, and researchers are starting to recognize graphene’s unique properties. Graphene is a single atomic layer of graphite, and graphite is a three-dimensional cube base structure of carbon. Graphite has a high conductivity rate, and graphene has an even higher conductivity, meaning that graphene makes for an excellent resistor in any hardware system. Graphene is flexible, has high durability, and can vary in resistance based on its shape (Sharon 2015). With graphene being able to change its resistivity, it can act as different types of sensors. These sensors include measuring pressure, resistance, force, strain, and angle. One problem across the globe is that patients have arthritis, decaying bone density, and injuries which can easily go mistreated or not treated at all. It can be hard to determine the severity of injuries in joints by observation of the patient. There are tools and equipment that will allow a doctor to track the force and degrees of motion of certain joints, but they are mostly limited to hospitals. With graphene acting as a sensor it can be embedded into casts, braces, and even clothing. With a mobile sensor that relays accurate and continuous data to a doctor they can more precisely determine a therapy or recovery time that will better suit the patients’ needs. In this project the graphene was used to measure the angle of a patient’s wrist while they were wearing a wrist brace. From the data collected, the graphene was able to track the user’s movement of their wrist as they moved it in a single direction. The data showed the angle of the wrist ranging from zero degrees to 90 degrees. This proves that graphene can shape the way biosensing is accomplished. Biodynamics is a growing field, and with more injuries everyday it is important to study graphene and how it can be used to diagnose and prevent injuries related to joints. Graphene can be used as a biosensor which can then be implemented into a brace to allow for accurate biodynamic tracking.
ContributorsSweeten, William (Author) / Lockhart, Thurmon (Thesis director) / Helms Tillery, Stephen (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
The Atlantic razor clam burrows underground with effectiveness and efficiency by coordinating shape changings of its shell and foot. Inspired by the burrowing strategy of razor clams, this research is dedicated to developing a self-burrowing technology for active underground explorations by investigating the burrowing mechanism of razor clams from the

The Atlantic razor clam burrows underground with effectiveness and efficiency by coordinating shape changings of its shell and foot. Inspired by the burrowing strategy of razor clams, this research is dedicated to developing a self-burrowing technology for active underground explorations by investigating the burrowing mechanism of razor clams from the perspective of soil mechanics. In this study, the razor clam was observed to burrow out of sands simply by extending and contracting its foot periodically. This upward burrowing gait is much simpler than its downward burrowing gait, which also involves opening/closing of the shell and dilation of the foot. The upward burrowing gait inspired the design of a self-burrowing-out soft robot, which drives itself out of sands naturally by extension and contraction through pneumatic inflation and deflation. A simplified analytical model was then proposed and explained the upward burrowing behavior of the robot and razor clams as the asymmetric nature of soil resistances applied on both ends due to the intrinsic stress gradient of sand deposits. To burrow downward, additional symmetry-breaking features are needed for the robot to increase the resistance in the upward burrowing direction and to decrease the resistance in the downward burrowing direction. A potential approach is by incorporating friction anisotropy, which was then experimentally demonstrated to affect the upward burrowing of the soft robot. The downward burrowing gait of razor clams provides another inspiration. By exploring the analogies between the downward burrowing gait and in-situ soil characterization methods, a clam-inspired shape-changing penetrator was designed and penetrated dry granular materials both numerically and experimentally. Results demonstrated that the shell opening not only contributes to forming a penetration anchor by compressing the surrounding particles, but also reduces the foot penetration resistance temporally by creating a stress arch above the foot; the shell closing facilitates the downward burrowing by reducing the friction resistance to the subsequent shell retraction. Findings from this research shed lights on the future design of a clam-inspired self-burrowing robot.
ContributorsHuang, Sichuan (Author) / Tao, Junliang (Thesis advisor) / Kavazanjian, Edward (Committee member) / Marvi, Hamidreza (Committee member) / Zapata, Claudia (Committee member) / van Paassen, Leon (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Animals have always been a source of inspiration for real-life problems. The octopus is one such animal that has a lot of untapped potential. The octopus’s arm is without solid joints or bone structure and despite this it can achieve many complicated movements with virtually infinite degrees of freedom. This

Animals have always been a source of inspiration for real-life problems. The octopus is one such animal that has a lot of untapped potential. The octopus’s arm is without solid joints or bone structure and despite this it can achieve many complicated movements with virtually infinite degrees of freedom. This ability is made possible through the unique morphology of the arm. The octopus’s arm is divided into transverse, longitudinal, oblique, and circular muscle groups and each one has a unique muscle fiber orientation. The octopus’s arm is classified as a hydrostat because it maintains a constant volume while contracting with the help of its different muscle groups. These muscle groups allow elongation, shortening, bending, and twisting of the arm when they work in combination with each other. To confirm the role of transverse and longitudinal muscle groups, an electromyography (EMG) recording of these muscle groups was performed while an amputated arm of an Octopus bimaculoides was stimulated with an electrical signal to induce movement. Statistical analysis was performed on these results to confirm the roles of each muscle group quantitatively. Octopus arm morphology was previously assumed to be uniform along the arm. Through a magnetic resonance imaging (MRI) study at the proximal, middle, and distal sections of the arm this notion was disproven, and a new pattern was discovered. Drawing inspiration from this finding and previous octopus arm prototypes, 4 bio-inspired designs were conceived and tested in finite element analysis (FEA) simulations. Four tests in elongation, shortening, bending, and transverse-assisted bending movements were performed on all designs to compare each design’s performance. The findings in this study have applications in engineering and soft robotics fields for use cases such as, handling fragile objects, minimally invasive surgeries, difficult-to-access areas that require squeezing through small holes, and other novel cases.
ContributorsAhmadi, Salaheddin (Author) / Marvi, Hamidreza (Thesis advisor) / Fisher, Rebecca (Committee member) / Xu, Zhe (Committee member) / Arizona State University (Publisher)
Created2023