|Student||Report Title||Student||Report Title|
|Konstantin Avdashchenko||Design of a Wireless Emg||Demarcus Hamm||Energy Monitoring System|
|Conor O'Reilly and Joshua Hernandez||The Design and Implementation of a High-Density Surface Electromyogram Sensor Array for Neural Control Applications||Zachary Polen||A Simplified System for Analyzing Stop Consonant Acoustics|
|Eric Truslow||Xkl: A Tool for Speech Analysis|
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Advisor: Prof. Cotter
This project is an attempt to increase the intuitiveness of H.I.D.'s (Human Interface Devices) by incorporating sensors to detect muscle use. Emg (electromyography) signals can be received with little cost, however there has been little development of cost-efficient systems. This project aims to create a microcontroller based prototype that is capable of transceiving emg data. This system will be reliable, portable, cheap and open-source. A prototype has been built that is capable of transmitting the analog sensor information to a reader.
Advisor: Prof. Traver
This project combines research of the Smart Grid system and energy monitoring systems. The project will use an energy monitoring system to simulate smart meters that will be used in the Smart Grid system. We will do this by using an energy monitoring system to measure the energy consumption in the electrical engineering labs. The analysis of this data will provide us information that could lead to energy savings by making us more aware of wasteful energy use or helping to create an energy management system.
Conor O'Reilly and Joshua Hernandez
Advisor: Prof. Hanson
The Design and Implementation of a High-Density Surface Electromyogram Sensor Array for Neural Control Applications
The modern human interacts with machines and computers on a daily basis; however, nearly all of these devices have been developed to be controlled by basic physical input devices such as a keyboard and mouse. The goal of this project was to research and develop an unobtrusive myoelectric system which could be worn comfortably on the userís forearm and be used to wirelessly control a host of devices by recognizing certain finger gestures made by the wearer. This input method allows for relatively hands-free control which could be used when direct physical control of a device may be inappropriate or even dangerous, such as while driving. The underlying technology also permits for the relocation of the sensor to other parts of the body, so it would also be invaluable in aiding the paralyzed or otherwise physically disabled. We designed a three-step system which gathers EMG data from the wearer, digitizes and wirelessly transmits the signals, and analyzes the signals to detect the movement of each individual finger.
Advisor: Prof. Helen Hanson
Analysis of acoustic waveforms is a complex process that is necessary to understand how different subjects produce speech. This project looks to support a study of the characteristics of medial stop consonants in speech. It will help researchers understand why and how such stop consonants are produced. The current process used for analysis is primarily manual and the steps must be repeated for every waveform analyzed. Speech analysis can require looking at thousands of waveforms, so this analysis process needs to be expedited. We created a software program based system to make the analysis easier and more accurate for the researcher.
Our goal was to create a system that: 1. Semi-automates the labeling of speech events using Praat software. 2. Converts the Praat data into a MATLAB database. 3. Performs statistical analysis, duration computations, averaging computations and standard deviations of these measures. 4. Is flexible enough that it can easily be adapted for studies other than the current one.
This system should simplify the data analysis of acoustic waveforms for speech studies. The researcher enters a directory
of labeled waveforms, runs one or more scripts in MATLAB and the data desired by the researcher is output in table form.
Advisor: Prof. Hanson
Xkl is a speech analysis program that requires additional functionality to continue being used. This project addresses this issue by adding an annotation system, and a pitch contour display. Annotation allows researchers to describe portions of speech signals. The pitch contour shows the change in periodicity of a speech signal over time. Users will be able to use Xkl to examine speech in ways that were previously impossible in Xkl.