This repository contains a trial model implementation of Liquid Time Constant (LTC) networks for EEG data analysis, particularly focused on the emotions database provided by Jordan J. Bird on Kaggle. Traditional methods often struggle with the non-linear and dynamic nature of EEG signals.
LTC paper by Ramin Hasani: https://arxiv.org/abs/2006.04439.
link for the dataset: https://www.kaggle.com/datasets/birdy654/eeg-brainwave-dataset-feeling-emotions.
JORDAN J. BIRD provides the dataset used in the project, and the papers on the dataset : https://www.researchgate.net/publication/329403546_Mental_Emotional_Sentiment_Classification_with_an_EEG-based_Brain-machine_Interface https://www.researchgate.net/publication/335173767_A_Deep_Evolutionary_Approach_to_Bioinspired_Classifier_Optimisation_for_Brain-Machine_Interaction