EEG-Python Analysis

exios66.github.io/EEG-Python-Analysis/

EEG Visualization App

Overview

The EEG Visualization App is a comprehensive, user-friendly platform that integrates EEG data analysis with real-time visualization. It is designed to provide researchers, clinicians, and developers with an intuitive interface to preprocess, analyze, and visualize EEG data. This application leverages the power of Python, Node.js, React, and Flask to create a seamless and efficient workflow for EEG signal processing, offering both backend and frontend functionalities.

Key Technologies: Python 3.8+: Used for backend data processing and EEG analysis.

Node.js 14+: Enables the modern frontend and backend integration with real-time functionality.

React 17.0+: Powers the dynamic and interactive user interface.

Flask 2.0+: Facilitates a lightweight and scalable backend server.

MNE-Python: A robust library for EEG processing used for signal preprocessing, feature extraction, and artifact removal.

Features

Advanced EEG Data Processing: Seamlessly process large-scale EEG datasets with various analysis methods, including artifact removal and feature extraction.
Real-Time Data Visualization: View live updates as EEG data is processed, offering a real-time perspective on data trends and findings.
Interactive Analysis Controls: Users can adjust processing parameters and visual settings directly from the interface, allowing them to explore the data interactively.
Multi-Format EEG Support: Upload and analyze EEG data from diverse file formats, such as .edf, .fif, and .set.
Statistical Analysis: Generate statistical summaries, including spectral analysis and temporal features, to extract meaningful insights.
Web-Based Interface: A clean, responsive interface accessible through modern web browsers, requiring no additional software installations.

System Requirements

The following components must be installed to run the EEG Visualization App:

Backend Requirements:

Python: Version 3.8 or higher
Flask: Version 2.0 or higher
MNE-Python for EEG processing

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Last updated 24 days ago

EEG Visualization App

Overview

Key Technologies: Python 3.8+: Used for backend data processing and EEG analysis.

Node.js 14+: Enables the modern frontend and backend integration with real-time functionality.

React 17.0+: Powers the dynamic and interactive user interface.

Flask 2.0+: Facilitates a lightweight and scalable backend server.

MNE-Python: A robust library for EEG processing used for signal preprocessing, feature extraction, and artifact removal.

Features

Advanced EEG Data Processing: Seamlessly process large-scale EEG datasets with various analysis methods, including artifact removal and feature extraction.

Real-Time Data Visualization: View live updates as EEG data is processed, offering a real-time perspective on data trends and findings.

Interactive Analysis Controls: Users can adjust processing parameters and visual settings directly from the interface, allowing them to explore the data interactively.

Multi-Format EEG Support: Upload and analyze EEG data from diverse file formats, such as .edf, .fif, and .set.

Statistical Analysis: Generate statistical summaries, including spectral analysis and temporal features, to extract meaningful insights.

Web-Based Interface: A clean, responsive interface accessible through modern web browsers, requiring no additional software installations.

System Requirements

The following components must be installed to run the EEG Visualization App:

Backend Requirements:

Python: Version 3.8 or higher

Flask: Version 2.0 or higher

MNE-Python for EEG processing