The proposed project will design and develop advanced machine learning algorithms to identify neuromarkers that can be used for the prediction of epileptic seizures using data from wearable electroencephalography (EEG). The goal of this project is to provide computational infrastructure that can predict seizures with high sensitivity and low false positive rates, and can provide real-time continuous monitoring making it highly impactful for patients and caregivers.
Both traditional and deep-learning architectures are being investigated for this problem.
Methods
Method development for this work is ongoing.