Shaurya Sharma

Temporal and Spatial Characterization of EEG Slowing Activity Types

Started Jan. 12, 2023

Abstract or project description

Life-threatening diseases often remain undetected until irreversible consequences manifest. EEG slowing, a common phenomenon in diseases like epilepsy and dementia, also appears in other life-threatening conditions. In this study, we analyzed data samples from the Temple TUH dataset of EEG slowing to discern distinct characteristics within each EEG slowing instance. We identified characteristics such as generalized or focal slowing, and classified them into three categories. Through time-frequency analysis, frequency-domain clustering, time-domain clustering, and additional frequency analysis methods, we explored variations in EEG slowing patterns. Our findings indicate that quantitative EEG features may be pivotal in early disease detection, potentially opening avenues for disease-curing mechanisms. This study highlights the critical features of EEG slowing and how these features correlate to specific types of slowing, suggesting a promising path toward further findings, such as cures. A comprehensive understanding of the temporal and spatial aspects of EEG slowing may lead to further insights into the etiology of these diseases and facilitate future discoveries.