EEG Signal

Electroencephalography (EEG) signals, reflecting brain electrical activity, are central to understanding brain function and developing brain-computer interfaces (BCIs). Current research focuses on improving signal processing techniques, particularly artifact removal using methods like Empirical Mode Decomposition combined with machine learning, and developing advanced decoding methods using deep learning architectures such as transformers, variational autoencoders, and diffusion models for tasks ranging from visual decoding to emotion recognition and even imagined speech reconstruction. These advancements hold significant promise for improving the accuracy and reliability of EEG-based diagnostics, BCIs, and neuroergonomic studies, ultimately impacting healthcare, assistive technologies, and our understanding of the brain.

Papers

February 5, 2024

Improving EEG Signal Classification Accuracy Using Wasserstein Generative Adversarial Networks
Joshua Park, Priyanshu Mahey, Ore Adeniyi
EEG Signal EEG Classification Wasserstein Generative Adversarial Network Wasserstein Gan

January 19, 2024

EEG Based Generative Depression Discriminator
Ziming Mao, Hao wu, Yongxi Tan, Yuhe Jin
Depression Detection Depression Symptom Brain Activity EEG Signal Neural Signal

November 20, 2023

hvEEGNet: exploiting hierarchical VAEs on EEG data for neuroscience applications
Giulia Cisotto, Alberto Zancanaro, Italo F. Zoppis, Sara L. Manzoni
EEG Data EEG Signal Hierarchical VAE Neural Network Application EEG Reconstruction

November 13, 2023

Sample Dominance Aware Framework via Non-Parametric Estimation for Spontaneous Brain-Computer Interface
Byeong-Hoo Lee, Byoung-Hee Kwon, Seong-Whan Lee
Brain Signal EEG Signal

July 26, 2023

Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEG
Soowon Kim, Young-Eun Lee, Seo-Hyun Lee, Seong-Whan Lee
Probabilistic Model EEG Signal Diffusion Learning Conditional Autoencoder Imagined Speech

July 19, 2023

Perturbing a Neural Network to Infer Effective Connectivity: Evidence from Synthetic EEG Data
Peizhen Yang, Xinke Shen, Zongsheng Li, Zixiang Luo, Kexin Lou, Quanying Liu
Neural Network Evidence Piece EEG Signal Granger Causality Underlying Causal Effective Connectivity

July 9, 2023

Emotion Analysis on EEG Signal Using Machine Learning and Neural Network
S. M. Masrur Ahmed, Eshaan Tanzim Sabur
Neural Network Machine Learning Emotion Recognition Underlying Emotion Brain Signal EEG Signal

May 27, 2023

Inter Subject Emotion Recognition Using Spatio-Temporal Features From EEG Signal
Mohammad Asif, Diya Srivastava, Aditya Gupta, Uma Shanker Tiwary
Emotion Recognition Temporal Feature Affective Computing EEG Signal

May 19, 2023

EEG and EMG dataset for the detection of errors introduced by an active orthosis device
Niklas Kueper, Kartik Chari, Judith Bütefür, Julia Habenicht, Su Kyoung Kim, Tobias Rossol, Marc Tabie, Frank Kirchner, Elsa Andrea Kirchner
Data Detection Error Feedback EEG Signal Event Related Potential

May 14, 2023

Using EEG Signals to Assess Workload during Memory Retrieval in a Real-world Scenario
Kuan-Jung Chiang, Steven Dong, Chung-Kuan Cheng, Tzyy-Ping Jung
EEG Signal EEG Signal Analysis Memory Retrieval Heavy Workload Cognitive Ergonomics

April 21, 2023

Interpretable and Robust AI in EEG Systems: A Survey
Xinliang Zhou, Chenyu Liu, Zhongruo Wang, Liming Zhai, Ziyu Jia, Cuntai Guan, Yang Liu
Timely Survey Inherent Interpretability Interpretable Way EEG Signal Robust AI

April 12, 2023

Color-based classification of EEG Signals for people with the severe locomotive disorder
Ankit Shrestha, Bikram Adhikari
Person Name EEG Signal Motor Impairment

March 20, 2023

Relate auditory speech to EEG by shallow-deep attention-based network
Fan Cui, Liyong Guo, Lang He, Jiyao Liu, ErCheng Pei, Yujun Wang, Dongmei Jiang
EEG Signal Attention Based Deep EEG Signal Analysis Attention Based Network Relation Information Attention Based Correlation Module Deep Similarity

March 10, 2023

Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals
Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy, Lucas Drumetz, Thomas Moreau, Matthieu Kowalski, Nicolas Courty
Covariance Matrix Brain Age EEG Signal Sliced Wasserstein Distance Sliced Wasserstein Symmetric Positive Definite Matrix Multivariate Biosignals

March 6, 2023

EEG Synthetic Data Generation Using Probabilistic Diffusion Models
Giulio Tosato, Cesare M. Dalbagno, Francesco Fumagalli
Synthetic Data Diffusion Probabilistic Model EEG Data EEG Signal

February 17, 2023

Novel Epileptic Seizure Detection Techniques and their Empirical Analysis
Rabel Guharoy, Nanda Dulal Jana, Suparna Biswas, Lalit Garg
Seizure Detection Empirical Analysis EEG Signal Epilepsy Detection

December 13, 2022

November 7, 2022

EEG-Fest: Few-shot based Attention Network for Driver's Vigilance Estimation with EEG Signals
Ning Ding, Ce Zhang, Azim Eskandarian
Attention Network EEG Signal Shot Scenario Drowsiness Detection VidSGG Datasets

October 25, 2022

Towards emotion recognition for virtual environments: an evaluation of EEG features on benchmark dataset
M. L. Menezes, A. Samara, L. Galway, A. Sant'anna, A. Verikas, F. Alonso-Fernandez, H. Wang, R. Bond
Global Evaluation Emotion Recognition Benchmark Dataset Brain Electroencephalography EEG Signal Emotion Discovery Virtual Environment EEG Feature User Emotion Electroencephalogram Signal

EEG Signal

Papers

Improving EEG Signal Classification Accuracy Using Wasserstein Generative Adversarial Networks

EEG Based Generative Depression Discriminator

hvEEGNet: exploiting hierarchical VAEs on EEG data for neuroscience applications

Sample Dominance Aware Framework via Non-Parametric Estimation for Spontaneous Brain-Computer Interface

Diff-E: Diffusion-based Learning for Decoding Imagined Speech EEG

Perturbing a Neural Network to Infer Effective Connectivity: Evidence from Synthetic EEG Data

Emotion Analysis on EEG Signal Using Machine Learning and Neural Network

Inter Subject Emotion Recognition Using Spatio-Temporal Features From EEG Signal

EEG and EMG dataset for the detection of errors introduced by an active orthosis device

Using EEG Signals to Assess Workload during Memory Retrieval in a Real-world Scenario

Interpretable and Robust AI in EEG Systems: A Survey

Color-based classification of EEG Signals for people with the severe locomotive disorder

Relate auditory speech to EEG by shallow-deep attention-based network

Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals

EEG Synthetic Data Generation Using Probabilistic Diffusion Models

Novel Epileptic Seizure Detection Techniques and their Empirical Analysis

CropCat: Data Augmentation for Smoothing the Feature Distribution of EEG Signals

Classification of Distraction Levels Using Hybrid Deep Neural Networks From EEG Signals

EEG-Fest: Few-shot based Attention Network for Driver's Vigilance Estimation with EEG Signals

Towards emotion recognition for virtual environments: an evaluation of EEG features on benchmark dataset