Noise-resilient and interpretable epileptic seizure detection
Deep convolutional neural networks have recently emerged as a state-of-the art tool in detection of seizures. Such models offer the ability to extract complex nonlinear representations of an electroencephalogram (EEG) signal which can improve accuracy over methods relying on hand-crafted features. However, neural networks are susceptible to confounding artifacts commonly present in EEG signals and