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Grad School: Human Growth Horror - Creative Project Entry of an Action/Adventure Computer Game Designed to Experimentally Demonstrate Viable Engineering Concepts for Educational Purposes

Description

The action/adventure game Grad School: HGH is the final, extended version of a BME Prototyping class project in which the goal was to produce a zombie-themed game that teaches biomedical engineering concepts. The gameplay provides fast paced, exciting, and mildly

The action/adventure game Grad School: HGH is the final, extended version of a BME Prototyping class project in which the goal was to produce a zombie-themed game that teaches biomedical engineering concepts. The gameplay provides fast paced, exciting, and mildly addicting rooms that the player must battle and survive through, followed by an engineering puzzle that must be solved in order to advance to the next room. The objective of this project was to introduce the core concepts of BME to prospective students, rather than attempt to teach an entire BME curriculum. Based on user testing at various phases in the project, we concluded that the gameplay was engaging enough to keep most users' interest through the educational puzzles, and the potential for expanding this project to reach an even greater audience is vast.

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2014-05

BIOELECTRIC IMPEDANCE ANALYSIS AS A METHOD FOR QUANTITATIVE HYDRATION MEASUREMENT

Description

Volume depletion can lead to migraines, dizziness, and significant decreases in a subject's ability to physically perform. A major cause of volume depletion is dehydration, or loss in fluids due to an imbalance in fluid intake to fluid excretion. Because

Volume depletion can lead to migraines, dizziness, and significant decreases in a subject's ability to physically perform. A major cause of volume depletion is dehydration, or loss in fluids due to an imbalance in fluid intake to fluid excretion. Because proper levels of hydration are necessary in order to maintain both short and long term health, the ability to monitor hydration levels is growing in clinical demand. Although devices capable of monitoring hydration level exist, these devices are expensive, invasive, or inaccurate and do not offer a continuous mode of measurement. The ideal hydration monitor for consumer use needs to be characterized by its portability, affordability, and accuracy. Also, this device would need to be noninvasive and offer continuous hydration monitoring in order to accurately assess fluctuations in hydration data throughout a specified time period. One particular method for hydration monitoring that fits the majority of these criteria is known as bioelectric impedance analysis (BIA). Although current devices using BIA do not provide acceptable levels of accuracy, portability, or continuity in data collection, BIA could potentially be modified to fit many, if not all, desired customer specifications. The analysis presented here assesses the viability of using BIA as a new standard in hydration level measurement. The analysis uses data collected from 22 subjects using an existing device that employs BIA. A regression derived for estimating TBW based on the parameters of age, weight, height, sex, and impedance is presented. Using impedance data collected for each subject, a regression was also derived for estimating impedance based on the factors of age, weight, height, and sex. The derived regression was then used to calculate a new impedance value for each subject, and these new impedance values were used to estimate TBW. Through a paired-t test between the TBW values derived by using the direct measurements versus the calculated measurements of impedance, the two samples were found to be comparable. Considerations for BIA as a noninvasive measurement of hydration are discussed.

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2013-05

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Modeling of solid state transformer for the FREEDM system demonstration

Description

The Solid State Transformer (SST) is an essential component in the FREEDM system. This research focuses on the modeling of the SST and the controller hardware in the loop (CHIL) implementation of the SST for the support of the FREEDM

The Solid State Transformer (SST) is an essential component in the FREEDM system. This research focuses on the modeling of the SST and the controller hardware in the loop (CHIL) implementation of the SST for the support of the FREEDM system demonstration. The energy based control strategy for a three-stage SST is analyzed and applied. A simplified average model of the three-stage SST that is suitable for simulation in real time digital simulator (RTDS) has been developed in this study. The model is also useful for general time-domain power system analysis and simulation. The proposed simplified av-erage model has been validated in MATLAB and PLECS. The accuracy of the model has been verified through comparison with the cycle-by-cycle average (CCA) model and de-tailed switching model. These models are also implemented in PSCAD, and a special strategy to implement the phase shift modulation has been proposed to enable the switching model simulation in PSCAD. The implementation of the CHIL test environment of the SST in RTDS is described in this report. The parameter setup of the model has been discussed in detail. One of the dif-ficulties is the choice of the damping factor, which is revealed in this paper. Also the grounding of the system has large impact on the RTDS simulation. Another problem is that the performance of the system is highly dependent on the switch parameters such as voltage and current ratings. Finally, the functionalities of the SST have been realized on the platform. The distributed energy storage interface power injection and reverse power flow have been validated. Some limitations are noticed and discussed through the simulation on RTDS.

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Date Created
2014

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Development of the selection procedure of an insulating foam for its application in gas insulated transmission lines, demonstrated using syntactic foam

Description

Due to increasing integration of renewable resources in the power grid, an efficient high power transmission system is needed in the near future to transfer energy from remote locations to the load centers. Gas Insulated Transmission Line (GIL) is a

Due to increasing integration of renewable resources in the power grid, an efficient high power transmission system is needed in the near future to transfer energy from remote locations to the load centers. Gas Insulated Transmission Line (GIL) is a specialized high power transmission system, designed by Siemens, for applications requiring direct burial or vertical installation of the transmission line. GIL uses SF6 as an insulating medium. Due to unavoidable gas leakages and high global warming potential of SF6, there is a need to replace this insulating gas by some other possible alternative. Insulating foam materials are characterized by excellent dielectric properties as well as their reduced weight. These materials can find their application in GIL as high voltage insulators. Syntactic foam is a polymer based insulating foam. It consists of a large number of microspheres embedded in a polymer matrix.

The work in this thesis deals with the development of the selection proce-dure for an insulating foam for its application in GIL. All the steps in the process are demonstrated considering syntactic foam as an insulator. As the first step of the procedure, a small representative model of the insulating foam is built in COMSOL Multiphysics software with the help of AutoCAD and Excel VBA to analyze electric field distribution for the application of GIL. The effect of the presence of metal particles on the electric field distribution is also observed. The AC voltage withstand test is performed on the insulating foam samples according to the IEEE standards. The effect of the insulating foam on electrical parameters as well as transmission characteristics of the line is analyzed as the last part of the thesis. The results from all the simulations and AC voltage withstand test are ob-served to predict the suitability of the syntactic foam as an insulator in GIL.

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Date Created
2014

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An online monitoring and fault location methodology for underground power cables

Description

With the growing importance of underground power systems and the need for greater reliability of the power supply, cable monitoring and accurate fault location detection has become an increasingly important issue. The presence of inherent random fluctuations in power system

With the growing importance of underground power systems and the need for greater reliability of the power supply, cable monitoring and accurate fault location detection has become an increasingly important issue. The presence of inherent random fluctuations in power system signals can be used to extract valuable information about the condition of system equipment. One such component is the power cable, which is the primary focus of this research.

This thesis investigates a unique methodology that allows online monitoring of an underground power cable. The methodology analyzes conventional power signals in the frequency domain to monitor the condition of a power cable.

First, the proposed approach is analyzed theoretically with the help of mathematical computations. Frequency domain analysis techniques are then used to compute the power spectral density (PSD) of the system signals. The importance of inherent noise in the system, a key requirement of this methodology, is also explained. The behavior of resonant frequencies, which are unique to every system, are then analyzed under different system conditions with the help of mathematical expressions.

Another important aspect of this methodology is its ability to accurately estimate cable fault location. The process is online and hence does not require the system to be disconnected from the grid. A single line to ground fault case is considered and the trend followed by the resonant frequencies for different fault positions is observed.

The approach is initially explained using theoretical calculations followed by simulations in MATLAB/Simulink. The validity of this technique is proved by comparing the results obtained from theory and simulation to actual measurement data.

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Date Created
2016

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Noninvasive metabolic monitoring: an assessment of thermoelectric gas adsorption biosensors for acetone and ethanol detection in breath analysis

Description

In the search for chemical biosensors designed for patient-based physiological applications, non-invasive diagnostic approaches continue to have value. The work described in this thesis builds upon previous breath analysis studies. In particular, it seeks to assess the adsorptive

In the search for chemical biosensors designed for patient-based physiological applications, non-invasive diagnostic approaches continue to have value. The work described in this thesis builds upon previous breath analysis studies. In particular, it seeks to assess the adsorptive mechanisms active in both acetone and ethanol biosensors designed for breath analysis. The thermoelectric biosensors under investigation were constructed using a thermopile for transduction and four different materials for biorecognition. The analytes, acetone and ethanol, were evaluated under dry-air and humidified-air conditions. The biosensor response to acetone concentration was found to be both repeatable and linear, while the sensor response to ethanol presence was also found to be repeatable. The different biorecognition materials produced discernible thermoelectric responses that were characteristic for each analyte. The sensor output data is presented in this report. Additionally, the results were evaluated against a mathematical model for further analysis. Ultimately, a thermoelectric biosensor based upon adsorption chemistry was developed and characterized. Additional work is needed to characterize the physicochemical action mechanism.

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Date Created
2011

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Design of an automated validation environment for a radiation hardened MIPS microprocessor

Description

Ever reducing time to market, along with short product lifetimes, has created a need to shorten the microprocessor design time. Verification of the design and its analysis are two major components of this design cycle. Design validation techniques can be

Ever reducing time to market, along with short product lifetimes, has created a need to shorten the microprocessor design time. Verification of the design and its analysis are two major components of this design cycle. Design validation techniques can be broadly classified into two major categories: simulation based approaches and formal techniques. Simulation based microprocessor validation involves running millions of cycles using random or pseudo random tests and allows verification of the register transfer level (RTL) model against an architectural model, i.e., that the processor executes instructions as required. The validation effort involves model checking to a high level description or simulation of the design against the RTL implementation. Formal techniques exhaustively analyze parts of the design but, do not verify RTL against the architecture specification. The focus of this work is to implement a fully automated validation environment for a MIPS based radiation hardened microprocessor using simulation based approaches. The basic framework uses the classical validation approach in which the design to be validated is described in a Hardware Definition Language (HDL) such as VHDL or Verilog. To implement a simulation based approach a number of random or pseudo random tests are generated. The output of the HDL based design is compared against the one obtained from a "perfect" model implementing similar functionality, a mismatch in the results would thus indicate a bug in the HDL based design. Effort is made to design the environment in such a manner that it can support validation during different stages of the design cycle. The validation environment includes appropriate changes so as to support architecture changes which are introduced because of radiation hardening. The manner in which the validation environment is build is highly dependent on the specifications of the perfect model used for comparisons. This work implements the validation environment for two MIPS simulators as the reference model. Two bugs have been discovered in the RTL model, using simulation based approaches through the validation environment.

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Date Created
2011

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A study of energy management systems and its failure modes in smart grid power distribution

Description

The subject of this thesis is distribution level load management using a pricing signal in a smart grid infrastructure. The project relates to energy management in a spe-cialized distribution system known as the Future Renewable Electric Energy Delivery and Management

The subject of this thesis is distribution level load management using a pricing signal in a smart grid infrastructure. The project relates to energy management in a spe-cialized distribution system known as the Future Renewable Electric Energy Delivery and Management (FREEDM) system. Energy management through demand response is one of the key applications of smart grid. Demand response today is envisioned as a method in which the price could be communicated to the consumers and they may shift their loads from high price periods to the low price periods. The development and deployment of the FREEDM system necessitates controls of energy and power at the point of end use.

In this thesis, the main objective is to develop the control model of the Energy Management System (EMS). The energy and power management in the FREEDM system is digitally controlled therefore all signals containing system states are discrete. The EMS is modeled as a discrete closed loop transfer function in the z-domain. A breakdown of power and energy control devices such as EMS components may result in energy con-sumption error. This leads to one of the main focuses of the thesis which is to identify and study component failures of the designed control system. Moreover, H-infinity ro-bust control method is applied to ensure effectiveness of the control architecture. A focus of the study is cyber security attack, specifically bad data detection in price. Test cases are used to illustrate the performance of the EMS control design, the effect of failure modes and the application of robust control technique.

The EMS was represented by a linear z-domain model. The transfer function be-tween the pricing signal and the demand response was designed and used as a test bed. EMS potential failure modes were identified and studied. Three bad data detection meth-odologies were implemented and a voting policy was used to declare bad data. The run-ning mean and standard deviation analysis method proves to be the best method to detect bad data. An H-infinity robust control technique was applied for the first time to design discrete EMS controller for the FREEDM system.

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Date Created
2014

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Adaptive learning of neural activity during deep brain stimulation

Description

Parkinson's disease is a neurodegenerative condition diagnosed on patients with

clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated

number of patients living with Parkinson's disease around the world is seven

to ten million. Deep brain stimulation (DBS) provides

Parkinson's disease is a neurodegenerative condition diagnosed on patients with

clinical history and motor signs of tremor, rigidity and bradykinesia, and the estimated

number of patients living with Parkinson's disease around the world is seven

to ten million. Deep brain stimulation (DBS) provides substantial relief of the motor

signs of Parkinson's disease patients. It is an advanced surgical technique that is used

when drug therapy is no longer sufficient for Parkinson's disease patients. DBS alleviates the motor symptoms of Parkinson's disease by targeting the subthalamic nucleus using high-frequency electrical stimulation.

This work proposes a behavior recognition model for patients with Parkinson's

disease. In particular, an adaptive learning method is proposed to classify behavioral

tasks of Parkinson's disease patients using local field potential and electrocorticography

signals that are collected during DBS implantation surgeries. Unique patterns

exhibited between these signals in a matched feature space would lead to distinction

between motor and language behavioral tasks. Unique features are first extracted

from deep brain signals in the time-frequency space using the matching pursuit decomposition

algorithm. The Dirichlet process Gaussian mixture model uses the extracted

features to cluster the different behavioral signal patterns, without training or

any prior information. The performance of the method is then compared with other

machine learning methods and the advantages of each method is discussed under

different conditions.

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Date Created
2015

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3D printed glucose monitoring sensor

Description

The American Diabetes Association reports that diabetes costs $322 billion annually and affects 29.1 million Americans. The high out-of-pocket cost of managing diabetes can lead to noncompliance causing serious and expensive complications. There is a large market potential for a

The American Diabetes Association reports that diabetes costs $322 billion annually and affects 29.1 million Americans. The high out-of-pocket cost of managing diabetes can lead to noncompliance causing serious and expensive complications. There is a large market potential for a more cost-effective alternative to the current market standard of screen-printed self-monitoring blood glucose (SMBG) strips. Additive manufacturing, specifically 3D printing, is a developing field that is growing in popularity and functionality. 3D printers are now being used in a variety of applications from consumer goods to medical devices. Healthcare delivery will change as the availability of 3D printers expands into patient homes, which will create alternative and more cost-effective methods of monitoring and managing diseases, such as diabetes. 3D printing technology could transform this expensive industry. A 3D printed sensor was designed to have similar dimensions and features to the SMBG strips to comply with current manufacturing standards. To make the sensor electrically active, various conductive filaments were tested and the conductive graphene filament was determined to be the best material for the sensor. Experiments were conducted to determine the optimal print settings for printing this filament onto a mylar substrate, the industry standard. The reagents used include a mixture of a ferricyanide redox mediator and flavin adenine dinucleotide dependent glucose dehydrogenase. With these materials, each sensor only costs $0.40 to print and use. Before testing the 3D printed sensor, a suitable design, voltage range, and redox probe concentration were determined. Experiments demonstrated that this novel 3D printed sensor can accurately correlate current output to glucose concentration. It was verified that the sensor can accurately detect glucose levels from 25 mg/dL to 400 mg/dL, with an R2 correlation value as high as 0.97, which was critical as it covered hypoglycemic to hyperglycemic levels. This demonstrated that a 3D-printed sensor was created that had characteristics that are suitable for clinical use. This will allow diabetics to print their own test strips at home at a much lower cost compared to SMBG strips, which will reduce noncompliance due to the high cost of testing. In the future, this technology could be applied to additional biomarkers to measure and monitor other diseases.

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Date Created
2017