Pinky : interactively analyzing large EEG datasets
Name
965197110-MIT.pdf
Description
Full printable version
Size
3.62 MB
Format
Adobe PDF
Checksum (MD5)
084f33b9678a678b23c8b62d33fcbd70
Author(s)
Blum, Joshua (Joshua M.)
Advisor(s)
Samuel Madden.
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, I describe a system I designed and implemented for interactively analyzing large electroencephalogram (EEG) datasets. Trained experts, known as encephalographers, analyze EEG data to determine if a patient has experienced an epileptic seizure. Since EEG analysis is time intensive for large datasets, there is a growing corpus of unanalyzed EEG data. Fast analysis is essential for building a set of example data of EEG results, allowing doctors to quickly classify the behavior of future EEG scans. My system aims to reduce the cost of analysis by providing near real-time interaction with the datasets. The system has three optimized layers handling the storage, computation, and visualization of the data. I evaluate the design choices for each layer and compare three dierent implementations across dierent workloads.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 75-77).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
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