Date of Award
Bachelor of Science
The ability of electroencephalogram (EEG) to be used as a diagnostic device for acquired brain injuries (ABI) has been conceptualized previously. Averaged event-related potentials (ERP) derived from an EEG are suitable as markers of dysfunction however, distinctive properties in the frequency domain have not been established previously. In the present study, we examined pre- existing EEG signal data of healthy adults (HA), mild ABI (mABI), and severe ABI (sABI) human groups. Through Fourier analysis performed in MATLAB, we found that individuals in our sample population (n=80) were able to be categorized into their respective group based on common neuronal activity detected at specific electrode locations. The characteristic activity patterns of individuals with ABI were found to be related to the amplitude of their theta waves. This novel way of interpreting EEG with respect to ABI, could significantly inform the diagnostic criteria for ABIs; it may also offer a pragmatic way for non-professionals to quickly detect concussions or similar injuries in competing athletes. Further efforts to sonify such neural activity of interest may elucidate more characteristic trends of ABI.
Zarra, Michael, "Electroencephalogram as a diagnostic tool in acquired brain injury". Senior Theses, Trinity College, Hartford, CT 2019.
Trinity College Digital Repository, https://digitalrepository.trincoll.edu/theses/769