The "Epilepsy Monitoring Unit Signal and Data Science Program" is a cutting-edge initiative designed to enhance the clinical workflow within Epilepsy Monitoring Units (EMUs). The program, Â established in 2023, is directed by Dr. Tamilia with the support of Prof. Alexander Rotenberg (Director of the EMU at BCH).
This EMU Science Program focuses on developing and implementing advanced computational tools for signal and data analysis, with the goal of improving the interpretation and clinical utility of the data collected during patient monitoring. By harnessing the power of sophisticated signal processing techniques, machine learning and artificial intelligence, the program aims to provide deeper insights into the complex brain activity associated with epilepsy.
Through the integration of these innovative tools into the daily operations of the EMU, the EMU Science Program seeks to help clinicians localize epileptiform EEG patterns, refine diagnoses, and personalize treatment strategies more effectively. The ultimate objective is to improve patient outcomes by making the monitoring process more efficient, accurate, and actionable, enabling timely interventions and optimizing care for individuals with epilepsy.
The EMU Signal and Data Science Program represents a significant step forward in the ongoing effort to bridge the gap between cutting-edge research and real-world clinical practice in the management of epilepsy.