NeuroSuite

NeuroSuite is a React + Vite web app prototype for EEG-based features and emotion recognition. It provides a modular UI with components for visualization, authentication, and calls out to local or remote EEG/emotion analysis services.

Key features

• Interactive brain model and scene lighting controls
• EEG decoding and sleep-stage detection UI pages
• Emotion recognition and feature extraction interfaces
• Authentication (Sign Up / Log In) and profile pages
• Lightweight service layer for API calls to EEG/emotion endpoints

Tech stack

• React (JSX) + Vite for fast development and build
• CSS for styling (see src/index.css)
• Small modular service layer in src/services for network calls

Getting started

Prerequisites

• Node.js 18+ (or current LTS)
• npm (or yarn)

Install

npm install

Run (development)

npm run dev

Build (production)

npm run build

Project structure (important files)

• src/ — application source
  • src/main.jsx — app entry
  • src/App.jsx — main router / layout
  • src/components/ — UI pages and components (e.g., Dashboard.jsx, EEGDecoder.jsx, EmotionRecognizer.jsx)
  • src/context/AuthContext.jsx — authentication context/provider
  • src/services/ — API wrappers: api.js, auth.js, eegApi.js, emotionApi.js
• public/ — static assets
• vite.config.js — Vite config

Services and APIs

The app uses small service modules in src/services to separate HTTP logic from components. Update the base URLs and auth handling in these files to point at your backend or mock endpoints.

Deployment

Build the project (npm run build) and serve the contents of the dist/ folder with any static host (Netlify, Vercel, Surge, or a simple nginx/Apache server).

Contributing

Contributions are welcome. Suggested workflow:

1. Fork the repo
2. Create a feature branch
3. Open a PR with a description of changes

Suggested next steps

• Add README badges (build, lint, deploy)
• Provide environment examples (.env.example) for API endpoints
• Add tests and CI (GitHub Actions)

License

This project is provided as-is. Add an explicit license file if you plan to share or publish.

Contact

For questions or help, open an issue in the repository.

What NeuroSuite Does

NeuroSuite provides a developer-focused interface to upload, visualize, and analyze EEG data and audio/video inputs for emotion recognition. It exposes UI pages to:

• Upload EEG recordings and request classification or file metadata (/eeg-decoder).
• Analyze sleep stages through a dedicated detector (/sleep-detector).
• Run emotion recognition on audio/video/files and view per-sample results (/emotion-recognizer).
• Visualize application-level results and user statistics on the Dashboard.

The app keeps ML and signal-processing logic on server endpoints (see src/services/*.js), letting the front end focus on UX, data flow, and result visualization.

Why Use NeuroSuite

• Rapid prototyping: quickly connect your EEG or emotion-analysis model to a ready-made UI.
• Research-friendly: separates front-end visualization from back-end analysis so researchers can swap models without rewriting the UI.
• Demo and evaluation: useful for demos, user studies, or validating model outputs with real users.
• Educational: teaches data flow for biosignal applications — from file upload to result interpretation.

How it works (high level)

• The React front end provides pages and components under src/components/ and manages authentication via src/context/AuthContext.jsx.
• Network calls go through small service modules in src/services (api.js, eegApi.js, emotionApi.js) which call backend endpoints for classification, metadata extraction, and sleep-stage detection.
• Protected routes require authentication; tokens are stored in localStorage and attached to requests by the services.
• The backend is expected to expose REST endpoints for /eeg/* and /emotion/* (see src/services for exact routes); adjust API_BASE_URL in src/services/api.js to point at your server.