🩺 Health Monitor AI

Health Monitor AI is an AI-assisted healthcare web application that combines a Flask backend with an interactive multi-page frontend to provide:

• AI-based disease prediction
• Conversational healthcare assistance
• BMI and wellness tracking
• Yoga and exercise guidance
• Health quizzes and rewards
• Wellness-focused educational content

Originally developed as an academic healthcare platform, the project was upgraded in March 2026 with improved UI, wellness modules, and an enhanced AI chatbot experience.

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🚀 Features

🤖 AI Disease Prediction

Users can enter symptoms and receive disease predictions generated from a trained TensorFlow/Keras model.

Highlights

• Multi-symptom prediction
• Neural-network-based classification
• Fast inference using saved .keras model

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💬 AI Health Chatbot

An AI-powered healthcare chatbot integrated using the Groq API.

Features

• Conversational health assistance
• Context-aware responses
• Concise wellness guidance
• Medical safety reminders

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📊 BMI & Wellness Monitor

Interactive BMI calculator with personalized wellness suggestions.

Includes

• BMI score calculation
• Health category classification
• Simple fitness recommendations

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🧘 Yoga & Exercise Guidance

Wellness section with beginner-friendly exercises.

Categories

• Yoga
• Cardio
• Breathing exercises
• Strength workouts

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🧠 Health Quiz System

Interactive quiz module with:

• scoring system
• animated feedback
• wellness explanations

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🎁 Rewards System

Gamified reward interface where users can simulate redeeming wellness rewards.

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🍎 Food Recommendation Guide

Displays healthy Indian and continental food suggestions.

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🔐 Frontend Login Experience

Simple login flow with:

• localStorage session handling
• personalized navbar state
• lightweight frontend authentication

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🛠️ Tech Stack

Frontend

• HTML5
• CSS3
• JavaScript

Backend

• Python
• Flask
• Flask-CORS

AI / Machine Learning

• TensorFlow / Keras
• scikit-learn
• Pandas
• NumPy

APIs & Integrations

• Groq Chat Completions API

Deployment

• Procfile
• runtime.txt

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📂 Project Structure

Health-Care/
│
├── app.py
├── requirements.txt
├── runtime.txt
├── Procfile
├── disease_symptoms.csv
├── disease_prediction_model.keras
├── .env
│
└── Health-care-main/
    ├── Home.html
    ├── App.html
    ├── Chatbot.html
    ├── Monitor.html
    ├── Login.html
    ├── Feature.html
    ├── Food.html
    ├── Yoga.html
    ├── Quiz.html
    ├── Reward.html
    ├── Contact.html
    ├── About.html
    ├── App.css
    ├── App.js
    ├── Auth.js
    └── Images/

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⚙️ Backend API Endpoints

POST /login

Handles frontend login interaction.

Example Request

{
  "username": "user",
  "password": "password"
}

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POST /predict

Predicts disease from symptoms.

Example Request

{
  "symptoms": ["fever", "cough"]
}

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POST /chat

Processes chatbot conversation history and returns AI-generated health guidance.

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🧠 How the System Works

1️⃣ Disease Prediction Pipeline

• Symptom data loaded from disease_symptoms.csv
• Symptoms encoded using MultiLabelBinarizer
• Neural network trained using TensorFlow/Keras
• Prediction returned as highest probability disease

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2️⃣ AI Chatbot Workflow

• Frontend sends conversation history to /chat
• Backend constructs prompt
• Groq API generates response
• Response returned with safety disclaimer

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3️⃣ Frontend Experience

• Multi-page responsive healthcare UI
• Shared styling via App.css
• Interactive wellness modules
• localStorage-based personalization

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🖥️ Installation & Setup

Prerequisites

• Python 3.11+
• GROQ API Key

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Installation

1. Clone Repository

git clone <repository-url>

2. Create Virtual Environment

python -m venv venv

3. Activate Environment

Windows

venv\Scripts\activate

Linux / Mac

source venv/bin/activate

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4. Install Dependencies

pip install -r requirements.txt

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5. Create .env File

GROQ_API_KEY=your_groq_api_key_here

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6. Run Flask Server

python app.py

Server runs at:

http://localhost:7860

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🔄 Frontend API Configuration

The frontend currently points to hosted Hugging Face endpoints.

To use local Flask APIs, update fetch URLs inside:

• Health-care-main/App.html
• Health-care-main/Chatbot.html
• Health-care-main/Login.html

Replace hosted URLs with:

http://localhost:7860

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⚠️ Current Limitations

• Demo-style authentication
• No database integration
• Model retrains during startup
• Chatbot provides general guidance only
• Some UI encoding depends on editor encoding

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✨ March 2026 Updates

• Improved UI/UX
• Added Yoga & Exercise section
• Added Quiz & Rewards system
• Integrated Groq-powered chatbot
• Improved login flow
• Added wellness-focused pages

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🚀 Future Improvements

• Real authentication system
• Database integration
• Offline model training workflow
• Appointment booking system
• Better AI safety guardrails
• Unified frontend/backend deployment

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👨‍💻 Author

Aditya Prabhat Gupta , Ayush Singh , Bipin Singh , Aditya Singh B.Tech CSE (AI & ML) — RIT Roorkee

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⚠️ Disclaimer

This project is for academic and educational purposes only. It is not a substitute for professional medical advice, diagnosis, or treatment.