ECG Dashboard

The ECG Dashboard offers a state-of-the-art solution for detecting cardiac abnormalities in real-time. It continuously monitors and analyzes the patient's heart activity, providing valuable insights on rhythm, heartbeat, and other significant parameters.

Screenshot of the ECG Dashboard

Features

• Real-time visualization of ECG data.
• Early identification of conditions such as myocardial infarction, arrhythmia, and other cardiovascular diseases.
• Selectable lead options for tailored viewing.
• Backend integration with a Flask server and a comprehensive ECG database.
• User-friendly front-end interface optimized for healthcare professionals.

Technology Stack

• Frontend: Built using HTML, CSS, and JavaScript.
• Backend: Powered by Flask, a Python web framework, and supplemented with libraries like NumPy and WFDB for ECG data extraction and visualization.
• Data Source: Utilizes a 12-lead ECG database available from the PhysioNet website.

Prerequisites

• Python (>=3.6)
• pip
• A modern web browser

Setup and Installation

Back-End

1. Install Python: Download and install Python from the official website.

2. Install Required Python Packages: Run the command:

   pip install flask wfdb numpy flask_cors
   

Front-End

Option 1: Using VS Code's Live Server

1. Open the Project Folder in VS Code: Navigate to your project directory.
2. Install the Live Server Extension: Locate and install the Live Server extension from VS Code's extensions marketplace.
3. Launch the Dashboard: Right-click on index.html and select "Open with Live Server".

Option 2: Using a Web Browser

1. Locate the Dashboard File: Navigate to the project directory.

2. Open the Dashboard: Double-click on index.html.

   Note: Ensure associated resources, like function.js and style.css, reside in the same directory as index.html.

Usage

1. Start the Backend: Ensure the Flask server from the backend setup is running.
2. Launch the ECG Dashboard: Follow the Front-End setup guide to view the dashboard in your preferred browser.
3. Interact with the Dashboard: Select desired ECG leads from the dropdown menu and then click "Submit" to display the ECG graphs.

Contributing

For any contributions or major changes to the project, please start by opening an issue to discuss your ideas or proposed modifications. Collaboration is always welcome!