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advanced-signal-proc-audio-separation

Mixtures of two Audio signals were separated using FastICA algorithm

aircraft-battle

an aircraft battle game written with pygame

app-sigvisualizer

PyQt5 application for real time signal visualization

arl-eegmodels

This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow

bci-controlled-ur-manipulator

Python implementation of motor imagery real-time BCI paradigm for 3D control of UR5 manipulator and ROBOTIQ gripper, with unique control session paradigm.

bci_mi_csp_dnn

Classification algorithm based on motor imagery brain-computer interface

bcidatasetiv2a

This is a repository for BCI Competition 2008 dataset IV 2a fixed and optimized for python and numpy. This dataset is related with motor imagery

beng-thesis---motor-imagery-based-brain-computer-interface

This is the source codes from my B.Eng thesis titled "An Application of Electroencephalogram Signals Classification for Controlling a Mobile Robot".

braincomputerinterfaces

Variety of applications for BCI research

clinical-trials

cnbitkextra

cnn-bci

convolutional neural network motor imagery based brain computer interface

cnn-mi-bci

CNN-SAE program for MI-BCI classification. (Based on "Tabar et al-2016-J Neural Eng. A novel deep learning approach for classification of EEG motor imagery signals")

common-spatial-pattern-algorithm

Common spatial pattern (CSP) is a mathematical procedure used in signal processing for separating a multivariate signal into additive subcomponents which have maximum differences in variance between two windows. This algorithm is mainly used in motor imagery based BCI for processing EEG data.

decoding-eeg-during-ao-mi-me

In this study, we aim to investigate the decoding of continuous EEG rhythms during action observation (AO), motor imagery (MI), and motor execution (ME) for standing and sitting. We developed a behavioral task in which participants were instructed to perform both AO and MI/ME in regard to the actions of sit-to-stand and stand-to- sit. Our results demonstrated that the ERD was prominent during AO, whereas ERS was typical during MI at the alpha band across the sensorimotor area.

dplm

Dimensionality reduction based on distance preservation to local mean for symmetric positive definite matrices

dtaidistance

Time series distances: Dynamic Time Warping (DTW)

eeg-analysis-for-motor-imagery-application

eeg-classification

This project was a joint effort with the neurology labs at UNL and UCD Anschutz to use deep learning to classify EEG data.

eeg-motor-imagery-classification---ann

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

eeg-online-experiment-gui

EEG online experiment GUI

eeg-pre

Pre-Processing of EEG

eeg-system

A combination of a python GUI, ESP8266/arduino code and a PCB design to create a system for acquisition of biological signals

eeg_commonspatialpattern_csp

eeg_svm

An EEG dichotomy program file , using CSP and SVM.

eegclassification

Implementation of EEG signal classification.

eegcode

eegfaster

Python implementation of FASTER method for EEG artifact rejection

eegnet

[Old version] PyTorch implementation of EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces - https://arxiv.org/pdf/1611.08024.pdf

emg-lda-classification

Using rms feature and LDA to classify EMG signals into 5 different classes.