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- All Subjects: Electrical Engineering
- Member of: Theses and Dissertations
- 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 thesis dissertation presents design of portable low power Electrochemical Impedance Spectroscopy (EIS) system which can be used for biomedical applications such as tear diagnosis, blood diagnosis, or any other body-fluid diagnosis. Two design methodologies are explained in this dissertation (a) a discrete component-based portable low-power EIS system and (b) an integrated CMOS-based portable low-power EIS system. Both EIS systems were tested in a laboratory environment and the characterization results are compared. The advantages and disadvantages of the integrated EIS system relative to the discrete component-based EIS system are presented including experimental data. The specifications of both EIS systems are compared with commercially available non-portable EIS workstations. These designed EIS systems are handheld and very low-cost relative to the currently available commercial EIS workstations.
ContributorsGhorband, Vishal (Author) / Blain Christen, Jennifer (Thesis advisor) / Song, Hongjiang (Committee member) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2016
Description
Over the past fifty years, the development of sensors for biological applications has increased dramatically. This rapid growth can be attributed in part to the reduction in feature size, which the electronics industry has pioneered over the same period. The decrease in feature size has led to the production of microscale sensors that are used for sensing applications, ranging from whole-body monitoring down to molecular sensing. Unfortunately, sensors are often developed without regard to how they will be integrated into biological systems. The complexities of integration are underappreciated. Integration involves more than simply making electrical connections. Interfacing microscale sensors with biological environments requires numerous considerations with respect to the creation of compatible packaging, the management of biological reagents, and the act of combining technologies with different dimensions and material properties. Recent advances in microfluidics, especially the proliferation of soft lithography manufacturing methods, have established the groundwork for creating systems that may solve many of the problems inherent to sensor-fluidic interaction. The adaptation of microelectronics manufacturing methods, such as Complementary Metal-Oxide-Semiconductor (CMOS) and Microelectromechanical Systems (MEMS) processes, allows the creation of a complete biological sensing system with integrated sensors and readout circuits. Combining these technologies is an obstacle to forming complete sensor systems. This dissertation presents new approaches for the design, fabrication, and integration of microscale sensors and microelectronics with microfluidics. The work addresses specific challenges, such as combining commercial manufacturing processes into biological systems and developing microscale sensors in these processes. This work is exemplified through a feedback-controlled microfluidic pH system to demonstrate the integration capabilities of microscale sensors for autonomous microenvironment control.
ContributorsWelch, David (Author) / Blain Christen, Jennifer (Thesis advisor) / Muthuswamy, Jitendran (Committee member) / Frakes, David (Committee member) / LaBelle, Jeffrey (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2012