Research Projects

Traumatic brain injury (TBI) is a significant health concern in India, causing death and disability in the young working population. The burden of TBI is higher in the Indian subcontinent compared to the western population, and the population at risk is younger. Diagnosis and treatment of this neurological illness are limited by expertise and availability of diagnostic modalities in semi-urban and rural areas. The typical course of action for head injury patients is to go to the emergency room, where doctors thoroughly examine the patient before referring them for a computed tomography (CT) scan. CT scans can be expensive and take about 30 minutes to complete, but over 90% of head injury patients are found to be CT negative. Exposure to CT has a 24% higher total cancer incidence than those who were not exposed. Using an EEG classification system with automated algorithms for point of care head injury triaging would be an ideal solution. EEG is an electrophysiological technique for recording electrical activity from the human brain, with its main utility being to evaluate dynamic cerebral functioning. However, due to its complexity, EEG signals have never been used in routine practice or emergency room settings. Quantitative EEG (qEEG) analysis of EEG converts raw EEG signals into digital forms using transformation methods, making them easily administrable by individuals with no prior background. This alleviates the need for specialists to interpret and report EEG, saving valuable time in the diagnosis and treatment of neurological illnesses.