Brainwaves Template

Overview

The Brainwaves template demonstrates how to build a comprehensive brain mapping and movement analytics platform using Moose. It features real-time collection, analysis, and visualization of brainwave data from EEG devices like the Muse Headband, with support for both live device streaming and simulation using datasets.

Features

• Real-time brainwave data collection and analysis from EEG devices
• Live terminal dashboard with interactive charts and visualizations
• Session-based data logging and tracking
• Movement and relaxation state analysis
• Dual-application architecture (DAS + Brainmoose backend)
• Optional OpenAI-powered insights and analysis
• Support for both live device streaming and CSV simulation

Architecture

DAS: Data Acquisition Server

The Data Acquisition Server is a Node.js/TypeScript application that handles:

1. Real-time Data Ingestion

   • UDP/OSC data collection from Muse devices or simulators
   • Session-based CSV logging with unique identifiers

2. Live Analysis & Visualization

   • Terminal dashboard with real-time charts and tables
   • Brainwave band analysis (Alpha, Beta, Delta, Theta, Gamma)
   • Movement detection using accelerometer and gyroscope data

3. Data Forwarding

   • Automatic forwarding to Moose backend for storage and analytics

Brainmoose: Analytics & API Backend

The Moose-powered backend provides:

• Modular data ingestion and storage pipeline
• Advanced analytics blocks for movement scoring
• RESTful APIs for querying session insights
• Optional OpenAI GPT-4o integration for enhanced analysis
• ClickHouse-based data warehouse for complex queries

Getting Started

bash -i <(curl -fsSL https://fiveonefour.com/install.sh) moose

1. Create a new Moose project from the template:

moose init moose-brainwaves brainwaves
cd moose-brainwaves

2. Install dependencies for both applications:

# Install DAS dependencies
cd apps/das
npm install
 
# Install Brainmoose dependencies
cd ../brainmoose
npm install

3. Start with simulation (no device required):

# Download sample data
cd ../das
./download.sh
 
# Start DAS
npm run dev -- --sessionId=MyTestSession

4. In another terminal start the Moose analytics backend:

cd {project_root}/apps/brainmoose
moose dev

5. In another terminal run the simulation (no device required):

cd {project_root}/apps/das
./sim.sh brain_data_coding.csv

API Endpoints

The template exposes key API endpoints for accessing brainwave analytics:

• /consumption/sessionInsights
  • Parameters: sessions (comma-separated sessionId|sessionLabel pairs)
  • Returns: Movement scores and session analytics for specified sessions

Data Models

Brain Data Schema

interface BrainData {
  timestamp: DateTime;
  bandOn: boolean;
  acc: {
    x: number;
    y: number;
    z: number;
  };
  gyro: {
    x: number;
    y: number;
    z: number;
  };
  alpha: number;
  beta: number;
  delta: number;
  theta: number;
  gamma: number;
  ppm: {
    channel1: number;
    channel2: number;
    channel3: number;
  };
  sessionId: string;
}

Analytics & Insights

The template includes sophisticated analytics for:

Movement Analysis

• Accelerometer-based movement scoring
• Gyroscope rotation detection
• Combined movement metrics calculation

Brainwave Band Analysis

• Alpha wave relaxation indicators
• Beta wave focus measurements
• Delta, Theta, and Gamma band processing
• Real-time state classification

Session Scoring

Example movement score calculation:

SELECT
    sessionId,
    SUM(sqrt((arrayElement(acc, 1)^2) + (arrayElement(acc, 2)^2) + (arrayElement(acc, 3)^2))) AS acc_movement_score,
    SUM(sqrt((arrayElement(gyro, 1)^2) + (arrayElement(gyro, 2)^2) + (arrayElement(gyro, 3)^2))) AS gyro_movement_score
FROM Brain_0_0
WHERE sessionId = '1735785243'
GROUP BY sessionId;

Device Support

Muse Headband Integration

• Direct OSC data streaming support
• Real-time EEG signal processing
• Multi-channel brainwave analysis

Simulation Support

• CSV data playback for testing
• Sample datasets included
• Configurable replay speeds

Customization

You can customize the template by:

• Extending brainwave analysis algorithms
• Adding new visualization components to the terminal UI
• Implementing custom movement detection logic
• Integrating additional EEG devices or data sources
• Enhancing the OpenAI analysis prompts and insights
• Creating custom API endpoints for specific analytics needs

Educational Resources