Head Injury Prediction Using EEG Data

Traumatic brain injury (TBI) causes transitory metabolic imbalances due to interruption of axoplasmic flow produced by leaky cell membranes Early diagnosis following a TBI is crucial for appropriate medical therapy. This study investigates the viability of utilizing electroencephalography (EEG) data to predict head injuries. To determine the severity of traumatic brain injury (TBI) patients, computed tomography (CT) or magnetic resonance imaging (MRI) analysis is typically required. However, doing an MRI or CT scan on every potential patient is becoming more costly and time-consuming as the number of TBI patients rises. Thus, as a substitute method of determining severity in patients with mild traumatic brain injury (TBI), we explore the viability of combining electroencephalography (EEG) and artificial intelligence in this work. EEG is less expensive than MRI or CT. EEG has temporal resolution but not as high resolution as CT and MRI.