This course aims to teach everyone the basics of programming computers using Python.

This repository contains research code for the preprint "Generating realistic neurophysiological time series with denoising diffusion probabilistic models".

Paper reproduction: Instantaneous 3D EEG Signal Analysis Based on Empirical Mode Decomposition and the Hilbert–Huang Transform Applied to Depth of Anaesthesia

Classify Motor Execution EEG signals by Deep Convolutional Neural Network

The decoding of continuous EEG rhythms during action observation (AO), motor imagery (MI), and motor execution (ME) for standing and sitting. (IEEE Sensors Journal)

This repository contains a set of Matlab scripts to process EEG and EMG signals (feature extraction, spectral analysis, ...).

Extracting Kinematics Using Wearable Sensors Code

This toolbox offers 40 feature extraction methods (EMAV, EWL, MAV, WL, SSC, ZC, and etc.) for Electromyography (EMG) signals applications.

Matlab bindings for liblsl

Lab Stream Layer support with EMOTIV Brainwear

PsychoPy Experiments with Emotiv EEG Components

A new approach based on a 10-layer one-dimensional convolution neural network (1D-CNN) to classify five brain states (four MI classes plus a 'baseline' class) using a data augmentation algorithm a…

Python Brain-Computer Interface Software

Classification and Explanation Model of Brain Signal based on Deep Learning Model

Deep learning software to decode EEG, ECG or MEG signals

Classification of BCI competition VI dataset 2a using ANN by applying WPD and CSP for feature extraction

This toolbox offers 30 types of EEG feature extraction methods (HA, HM, HC, and etc.) for Electroencephalogram (EEG) applications.

Comparative analysis of pairwise interactions in multivariate time series.

NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing

Create behavioral experiments in a browser using JavaScript

Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python

Code and documentation for the winning sollution to the Grasp-and-Lift EEG Detection challenge

A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

A list of all public EEG-datasets

Helper functions for various signal processing projects

NMA Computational Neuroscience course

NMA deep learning course

My continuously updated Machine Learning, Probabilistic Models and Deep Learning notes and demos (2000+ slides) 我不间断更新的机器学习，概率模型和深度学习的讲义(2000+页)和视频链接

Wasserstein GAN TensorFlow Implementation