Skip to content

Latest commit

 

History

History
87 lines (69 loc) · 4.35 KB

README.md

File metadata and controls

87 lines (69 loc) · 4.35 KB

Welcome to the EEG Analysis Platform! 🧠⚡

This repository contains interactive EEG analysis web application, an easy-to-use tool to visualize and analyze EEG signals using complexity and entropy.

Streamlit Plotly Pandas NumPy SciPy PyWavelets NeuroKit2

The main functionalities of the platform at the moment are:

  • Visualization of EEG signals
  • Frequency analysis using wavelets
  • Entropy analysis.

Features ✨

⚡ EEG Visualization

Load and visualize EEG signals from the Fp1 and Fp2 channels, allowing you to analyze the signals over specific time intervals.

📡 Frequency Analysis

Perform wavelet-based frequency analysis on EEG signals. This feature allows you to explore the frequency spectrum over time and analyze dynamic changes in brainwave frequencies.

📊 Entropy Analysis

Evaluate the complexity of EEG signals by computing entropy measures, such as Shannon Entropy, Approximate Entropy, and Sample Entropy.

EEG Signal Acquisition ⚙️

The EEG data used in this project was acquired with the BITalino NeuroBIT Kit. Electrodes were placed following the international 10-20 system, specifically at Fp1 or Fp2 for brain activity measurement. The reference electrode was placed behind the ear.

Electrode Positioning

Electrode positioning for EEG at Fp1: Measuring pins IN+/- (left) and reference (right).

How to Use 🔧

  1. Clone the repository: 
    git clone https://github.com/Seba3995/EEG_web_app.git
  2. Install the required dependencies: 
    pip install -r requirements.txt
  3. Run the app: 
    streamlit run Home.py

Project Structure

EEG_Analysis_Platform/
│
├── components/                    # Directory for component classes
│   ├── data_loader.py             # Class for loading EEG data
│   ├── entropy_analyzer.py        # Class for performing entropy analysis
│   ├── ui_elements.py             # Class for displaying UI elements (e.g., logos)
│   ├── visualizer.py              # Class for visualizing EEG signals and analysis results
│   ├── wavelet_analyzer.py        # Class for performing wavelet-based frequency analysis
│
├── data/                          # Directory for storing CSV EEG data files
│   └── eeg_data.csv               # Example EEG data file (replace with your own data)
│
├── pages/                         # Directory for different app functionalities
│   ├── 1_⚡_Visualización_EEG.py   # Page for EEG signal visualization
│   ├── 2_📡_Análisis_Frecuencial.py# Page for frequency analysis using wavelets
│   ├── 3_📊_Analisis_Entropía.py   # Page for entropy analysis
│
├── Home.py                        # Main landing page with tabbed navigation
├── requirements.txt               # List of dependencies to install
└── README.md                      # Project documentation (this file)

Architecture Overview

This platform follows a component-based architecture where each functionality is encapsulated in its own class, ensuring modularity, scalability, and maintainability.

Main Components

  • EEGDataLoader: Handles loading EEG data from CSV files.
  • EEGVisualizer: Provides functions to visualize EEG data and results.
  • EntropyAnalyzer: Calculates various entropy metrics for EEG signals.
  • EEGWaveletAnalyzer: Performs continuous wavelet transformation to analyze the frequency content of EEG signals.
  • UIElements: Displays reusable UI elements like logos and headings.

Feel free to contribute, and let me know if you encounter any issues! 😄