VitalFlow Backend

VitalFlow is a health monitoring system that integrates health data from Android devices using Flutter and Kotlin, processes it through a Flask-based backend, and stores insights in a MongoDB database. This backend handles API endpoints for health metrics like steps, heart rate, sleep, hydration, stress levels, and daily performance.

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Features

• User Authentication (Signup/Login with bcrypt password hashing)
• Health Data Syncing from Health Connect (Steps, Heart Rate, Sleep, etc.)
• Water Intake Logging (Manual and estimated via NLP)
• Stress Detection (Text-based and calculated from vitals)
• Sleep Monitoring using bedtime schedule
• Performance & Insights Engine combining metrics
• Data Visualization Support for graphs and trends (via API)

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Tech Stack

Layer	Tech
Backend	Python, Flask
Database	MongoDB
Auth	Bcrypt, JWT (optional)
API Design	RESTful
NLP Model	Scikit-learn / SpaCy / Custom ML
Platform	Android (Flutter & Kotlin)

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Project Structure

vitalflow_backend/
│
├── app/
│   ├── __init__.py
│   ├── routes/
│   │   ├── auth.py
│   │   ├── health_data.py
│   │   ├── water_log.py
│   │   ├── stress_log.py
│   │   └── insights.py
│   ├── models/
│   │   ├── user.py
│   │   ├── health.py
│   │   └── utils.py
│   └── nlp/
│       ├── water_parser.py
│       └── stress_analyzer.py
│
├── config.py
├── requirements.txt
├── run.py
└── README.md

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Getting Started

1. Clone the Repository

git clone https://github.com/B-Acharekar/vitalflow_backend.git
cd vitalflow_backend

2. Create a Virtual Environment

python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Configure Environment Variables

Create a .env file in the root directory with the following content:

MONGO_URI=mongodb://localhost:27017/vitalflow
SECRET_KEY=your-secret-key

5. Run the Server

python run.py

Server runs at http://localhost:5000/

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API Endpoints Overview

Method	Endpoint	Description
POST	/signup	Register a new user
POST	/login	Authenticate user
POST	/health/steps	Log step data
POST	/health/heart-rate	Log heart rate
POST	/health/sleep	Log sleep duration
POST	/water/log	Log water intake
POST	/stress/analyze	Log and analyze stress input
GET	/insights/day	Get daily performance insights

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NLP and Stress Estimation

• Water Intake Parsing: Converts phrases like "drank a glass of water" into estimated ml values.
• Stress Detection: Based on sentiment analysis or derived from heart rate and sleep data.

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Future Improvements

• Add unit and integration tests
• Add Swagger/OpenAPI documentation
• Dockerize for containerized deployment
• Implement CI/CD pipeline