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a-compact-and-interpretable-convolutional-neural-network-for-single-channel-eeg

In this project, we propose a CNN model to classify single-channel EEG for driver drowsiness detection. We use the Class Activation Map (CAM) method for visualization. Results show that the model not only has a high accuracy but also learns biologically explainable features, e.g., Alpha spindles and Theta burst, as evidence for the drowsy state.

academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

attnsleep

[IEEE TNSRE] "An Attention-based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG"

awesome-ai-for-time-series-papers

A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.

bciciv2a-fbcsp

Implementation of filter bank common spatial pattern (FBCSP) for MI-based BCI in python

cfc

Closed-form Continuous-time Neural Networks

ds-ddpm

Implementation of Domain Specific Denoising Diffusion Probabilistic Models for Brain Dynamics/EEG Signals

eeg-based-cross-subject-driver-drowsiness-recognition-with-an-interpretable-cnn

Existing work in the field of BCI treats deep learning models as black-box classifiers. In this project, we develop a novel model named "InterpretableCNN" that allows sample wise analysis of important features for classification. The model not only achieves SOTA classification accuracy of EEG signals but also reveals meaningful features from EEG.

eeg-dqn

The repo contains the code for the paper "EEG-based Drowsiness Estimation for Safety Driving using Deep Q-Learning" submitted to TETCI and currently under revision

fbcnet

FBCNet: An Efficient Multi-view Convolutional Neural Network for Brain-Computer Interface

fedformer

image

lift-cam

Code for the ICCV 2021 paper: "Towards Better Explanations of Class Activation Mapping"

mind-vis

Code base for MinD-Vis

python

最良心的 Python 教程：

raindrop

Graph Neural Networks for Irregular Time Series

sleep-stage-classification-papers

This repo contains a list of papers for sleep stage classification using deep learning based techniques starting from 2017-afterwards. I classified them generally according to the proposed technique.

survey

This is a repository contains materials for future survey submission

ts-tcc

[IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"

tsai

Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai

xinliangzhou.github.io

yasa

YASA (Yet Another Spindle Algorithm): a Python package to analyze polysomnographic sleep recordings.