Extracting Interpretable EEG Features from a Deep Learning Model to Assess the Quality of Human-Robot Co-manipulation

There is an increasing interest in adapting the deep learning models into neuroimaging techniques such as electroencephalogram (EEG). However, one of the fundamental problems in deep learning models is the interpretability of the learned representations. Even though many interpretability models exist for computer vision applications, adapting those methods for deep learning using EEG is still a ch...