Tutorials

• EEGUnity: Supporting Multi-Modal Data
  • Special Notes
  • Multimodal Support
  • Custom Batch Processing
  • Recommendations
• Formatting Channel Names and Inspecting Metadata
  • Requirements
  • Steps
    • Step 1: Load the Dataset
    • Step 2: Save the Initial Locator File
    • Step 3: Select EEG data
    • Step 4: Format Channel Names
    • Step 7: Reload the Dataset
• Creating a Standardized FIF Dataset using EEGUnity
  • Prerequisites
  • Purpose
  • 🚀 Step 0: Prepare a Python Environment
  • Step 1 Prepare a Python Project
  • Step 2 Make Standard Script for Datasets
  • Detailed Explanation of the Code
  • Key Points to Remember
• Cooperation with Multiple Computers or Servers using EEGUnity
  • Prerequisites
  • Assumptions
  • For Researcher A
  • For Researcher B
• EEG Dataset Processing Tutorial
  • Demo 1: Detailed Processing Workflow (demo_make_h5Dataset.py)
    • Key Steps:
    • Code:
  • Demo 2: Quick Batch Processing (demo_make_h5Dataset_quick.py)
    • Key Steps:
    • Code:
• Reading EEGUnity HDF5 Files: A Guide
  • 1. Introduction
  • 2. What is HDF5?
  • 3. Understanding Data Saving in HDF5
  • 4. Sample Script to Read HDF5 Files
• Speeding Up EEGUnity Processing with Multithreading
  • 1. Introduction
  • 2. When to Use Multithreading
  • 3. Step-by-Step Guide
    • Step 1: Group Dataset by Domain
    • Step 2: Define the Task Function
    • Step 3: Run Tasks with ThreadPoolExecutor
  • 4. Summary