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Electroencephalography Feature Extraction of Neural Stimuli

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Many mysteries still surround brain function, and yet greater understanding of it is vital to advancing scientific research. Studies on the brain in particular play a huge role in the medical field as analysis can lead to proper diagnosis of patients and to anticipatory treatments. The objective of this research…

Many mysteries still surround brain function, and yet greater understanding of it is vital to advancing scientific research. Studies on the brain in particular play a huge role in the medical field as analysis can lead to proper diagnosis of patients and to anticipatory treatments. The objective of this research was to apply signal processing techniques on electroencephalogram (EEG) data in order to extract features for which to quantify an activity performed or a response to stimuli. The responses by the brain were shown in eigenspectrum plots in combination with time-frequency plots for each of the sensors to provide both spatial and temporal frequency analysis. Through this method, it was revealed how the brain responds to various stimuli not typically used in current research. Future applications might include testing similar stimuli on patients with neurological diseases to gain further insight into their condition.
ContributorsJackson, Matthew Joseph (Author) / Bliss, Daniel (Thesis director) / Berisha, Visar (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Audio Waveform Sample SVD Compression and Impact on Performance

Description

Lossy compression is a form of compression that slightly degrades a signal in ways that are ideally not detectable to the human ear. This is opposite to lossless compression, in which the sample is not degraded at all. While lossless compression may seem like the best option, lossy compression, which…

Lossy compression is a form of compression that slightly degrades a signal in ways that are ideally not detectable to the human ear. This is opposite to lossless compression, in which the sample is not degraded at all. While lossless compression may seem like the best option, lossy compression, which is used in most audio and video, reduces transmission time and results in much smaller file sizes. However, this compression can affect quality if it goes too far. The more compression there is on a waveform, the more degradation there is, and once a file is lossy compressed, this process is not reversible. This project will observe the degradation of an audio signal after the application of Singular Value Decomposition compression, a lossy compression that eliminates singular values from a signal’s matrix.
ContributorsHirte, Amanda (Author) / Kosut, Oliver (Thesis director) / Bliss, Daniel (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05