Skip to content

lokashrinav/earEchoStream

Repository files navigation

EarEcho - Sideline Concussion Screening System

A revolutionary 15-second concussion screening application using otoacoustic emissions measured through consumer wireless earbuds.

Overview

EarEcho provides rapid, objective brain injury assessment through a simple audio test that measures inner ear responses. The system delivers immediate traffic light results (Green/Yellow/Red) for sideline screening.

Key Features

  • 15-Second Test: Quick objective measurement vs traditional 15-minute subjective tests
  • Consumer Hardware: Uses standard wireless earbuds with built-in microphones
  • Traffic Light Results: Clear Green/Yellow/Red risk assessment
  • Player Management: Optional athlete tracking and baseline comparison
  • Data Analytics: Test history and trend analysis

Technology

Based on peer-reviewed research from Nature Biomedical Engineering demonstrating that consumer earbuds can achieve medical-grade otoacoustic emission measurement accuracy.

Demo Version

This is a proof-of-concept demonstration that simulates the otoacoustic emission measurement process. Full implementation would require:

  • WebRTC audio capture from earbud microphones
  • Real-time signal processing and FFT analysis
  • Calibrated clinical thresholds

Setup

  1. Install dependencies:
pip install streamlit numpy pandas scipy plotly sqlalchemy
  1. Run the application:
streamlit run app.py --server.port 5000

Research Foundation

  • Nature Biomedical Engineering study on consumer earbud capabilities
  • Otoacoustic emission changes in traumatic brain injury
  • $50 solution vs $5000 traditional equipment

License

Proof of concept for educational and research purposes.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages