NeuroSync - EEG Brain-Computer Interface System

Syncing Minds with Machines

Advanced MATLAB-based EEG signal processing and Brain-Computer Interface implementation

Features • Installation • Quick Start • Examples • Documentation

Overview

NeuroSync is a comprehensive EEG Brain-Computer Interface (BCI) system implemented in MATLAB. It provides a complete pipeline for EEG signal processing, feature extraction, machine learning classification, and real-time BCI applications.

Key Capabilities

• Complete EEG Processing Pipeline from raw signals to classification
• Real-time BCI Interface with visual feedback
• Multiple ML Models (SVM, Random Forest, LDA, Neural Networks)
• Comprehensive Visualization Dashboard
• Simulated & Real EEG Data Support

Features

Signal Processing

• ✅ Bandpass & notch filtering
• ✅ Artifact detection & removal (eye blinks, muscle artifacts)
• ✅ Common Average Reference (CAR)
• ✅ ICA for component analysis
• ✅ Time-frequency analysis

Feature Extraction

• ✅ Time-domain features (mean, variance, skewness, kurtosis)
• ✅ Frequency-domain features (band powers, spectral edge)
• ✅ Hjorth parameters
• ✅ Connectivity features
• ✅ Custom feature sets

Machine Learning

• ✅ Support Vector Machines (SVM)
• ✅ Random Forest
• ✅ Linear Discriminant Analysis (LDA)
• ✅ Neural Networks
• ✅ Ensemble methods
• ✅ Cross-validation & hyperparameter tuning

Visualization

• ✅ Real-time EEG display
• ✅ Topographical brain maps
• ✅ Time-frequency representations
• ✅ Classification results dashboard
• ✅ Interactive BCI interface

Installation

Prerequisites

• MATLAB R2020b or later
• Signal Processing Toolbox
• Statistics and Machine Learning Toolbox
• (Optional) Deep Learning Toolbox
• (Optional) EEGLAB (for advanced ICA)

Setup

1. Clone the repository:

git clone https://github.com/Fogyvishnu/NeuroSync.git
cd NeuroSync

2. Add to MATLAB Path

addpath(genpath(pwd));
savepath;  % Optional: save path for future sessions

4. Run Setup Script

setup_neurosync;