Investigation of Machine Learning Approaches for Traumatic Brain Injury Classification via EEG Assessment in Mice

Traumatic brain injury (TBI) is a common cause of disability and death in young people [1]. Caused by external impact such as blunt trauma, penetrating objects or blast waves to the head, TBI is becoming increasingly prevalent with an estimated 1.6 million individuals sustaining mild traumatic brain injury (mTBI) each year. Major causes of TBI have been vehicle related collisions, sports or combat injuries causing brain damages, including tearing injuries of white matter or hematomas resulting in nausea, disturbed sleep patterns [2], dizziness, memory and/or concentration problems, emotional disturbances and seizures. Many of whom are never hospitalized and may suffer from consequences of head injury. Lack of consensus regarding what constitutes mTBI adds to the complication of the under-diagnosis of the disease [3].