Matching Items (4)
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- All Subjects: 3D Printing
- Creators: LaBelle, Jeffrey
- Resource Type: Text
Description
Bioscience High School, a small magnet high school located in Downtown Phoenix and a STEAM (Science, Technology, Engineering, Arts, Math) focused school, has been pushing to establish a computer science curriculum for all of their students from freshman to senior year. The school's Mision (Mission and Vision) is to: "..provide a rigorous, collaborative, and relevant academic program emphasizing an innovative, problem-based curriculum that develops literacy in the sciences, mathematics, and the arts, thus cultivating critical thinkers, creative problem-solvers, and compassionate citizens, who are able to thrive in our increasingly complex and technological communities." Computational thinking is an important part in developing a future problem solver Bioscience High School is looking to produce. Bioscience High School is unique in the fact that every student has a computer available for him or her to use. Therefore, it makes complete sense for the school to add computer science to their curriculum because one of the school's goals is to be able to utilize their resources to their full potential. However, the school's attempt at computer science integration falls short due to the lack of expertise amongst the math and science teachers. The lack of training and support has postponed the development of the program and they are desperately in need of someone with expertise in the field to help reboot the program. As a result, I've decided to create a course that is focused on teaching students the concepts of computational thinking and its application through Scratch and Arduino programming.
ContributorsLiu, Deming (Author) / Meuth, Ryan (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Electromyography (EMG) and Electroencephalography (EEG) are techniques used to detect electrical activity produced by the human body. EMG detects electrical activity in the skeletal muscles, while EEG detects electrical activity from the scalp. The purpose of this study is to capture different types of EMG and EEG signals and to determine if the signals can be distinguished between each other and processed into output signals to trigger events in prosthetics. Results from the study suggest that the PSD estimates can be used to compare signals that have significant differences such as the wrist, scalp, and fingers, but it cannot fully distinguish between signals that are closely related, such as two different fingers. The signals that were identified were able to be translated into the physical output simulated on the Arduino circuit.
ContributorsJanis, William Edward (Author) / LaBelle, Jeffrey (Thesis director) / Santello, Marco (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-12
Description
This paper summarizes the [1] ideas behind, [2] needs, [3] development, and [4] testing of 3D-printed sensor-stents known as Stentzors. This sensor was successfully developed entirely from scratch, tested, and was found to have an output of 3.2*10-6 volts per RMS pressure in pascals. This paper also recommends further work to render the Stentzor deployable in live subjects, including [1] further design optimization, [2] electrical isolation, [3] wireless data transmission, and [4] testing for aneurysm prevention.
ContributorsMeidinger, Aaron Michael (Author) / LaBelle, Jeffrey (Thesis director) / Frakes, David (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
Description
The advent of medical imaging has enabled significant advances in pre-procedural planning, allowing cardiovascular anatomy to be visualized noninvasively before a procedure. However, absolute scale and tactile information are not conveyed in traditional pre-procedural planning based on images alone. This information deficit fails to completely prepare clinicians for complex heart repair, where surgeons must consider the varied presentations of cardiac morphology and malformations. Three-dimensional (3D) visualization and 3D printing provide a mechanism to construct patient-specific, scale models of cardiovascular anatomy that surgeons and interventionalists can examine prior to a procedure. In addition, the same patient-specific models provide a valuable resource for educating future medical professionals. Instead of looking at idealized images on a computer screen or pages from medical textbooks, medical students can review a life-like model of patient anatomy.
In cases where surgical repair is insufficient to return the heart to normal function, a patient may proceed to advanced heart failure, and a heart transplant may be required. Unfortunately, a finite number of available donor hearts are available. A mechanical circulatory support (MCS) device can be used to bridge the time between heart failure and reception of a donor heart. These MCS devices are typically constructed for the adult population. Accordingly, the size associated to the device is a limiting factor for small adults or pediatric patients who often have smaller thoracic measurements. While current eligibility criteria are based on correlative measurements, the aforementioned 3D visualization capabilities can be leveraged to accomplish patient-specific fit analysis.
The main objectives of the work presented in this dissertation were 1) to develop and evaluate an optimized process for 3D printing cardiovascular anatomy for surgical planning and medical education and 2) to develop and evaluate computational tools to assess MCS device fit in specific patients. The evaluations for objectives 1 and 2 were completed with a collection of qualitative and quantitative validations. These validations include case studies to illustrate meaningful, qualitative results as well as quantitative results from surgical outcomes. The latter results present the first quantitative supporting evidence, beyond anecdotal case studies, regarding the efficacy of 3D printing for pre-procedural planning; this data is suitable as pilot data for clinical trials. The products of this work were used to plan 200 cardiovascular procedures (including 79 cardiothoracic surgeries at Phoenix Children's Hospital), via 3D printed heart models and assess MCS device fit in 29 patients across 6 countries.
In cases where surgical repair is insufficient to return the heart to normal function, a patient may proceed to advanced heart failure, and a heart transplant may be required. Unfortunately, a finite number of available donor hearts are available. A mechanical circulatory support (MCS) device can be used to bridge the time between heart failure and reception of a donor heart. These MCS devices are typically constructed for the adult population. Accordingly, the size associated to the device is a limiting factor for small adults or pediatric patients who often have smaller thoracic measurements. While current eligibility criteria are based on correlative measurements, the aforementioned 3D visualization capabilities can be leveraged to accomplish patient-specific fit analysis.
The main objectives of the work presented in this dissertation were 1) to develop and evaluate an optimized process for 3D printing cardiovascular anatomy for surgical planning and medical education and 2) to develop and evaluate computational tools to assess MCS device fit in specific patients. The evaluations for objectives 1 and 2 were completed with a collection of qualitative and quantitative validations. These validations include case studies to illustrate meaningful, qualitative results as well as quantitative results from surgical outcomes. The latter results present the first quantitative supporting evidence, beyond anecdotal case studies, regarding the efficacy of 3D printing for pre-procedural planning; this data is suitable as pilot data for clinical trials. The products of this work were used to plan 200 cardiovascular procedures (including 79 cardiothoracic surgeries at Phoenix Children's Hospital), via 3D printed heart models and assess MCS device fit in 29 patients across 6 countries.
ContributorsRyan, Justin Robert (Author) / Frakes, David (Thesis advisor) / Collins, Daniel (Committee member) / LaBelle, Jeffrey (Committee member) / Pizziconi, Vincent (Committee member) / Pophal, Stephen (Committee member) / Arizona State University (Publisher)
Created2015