AI-Enabled Posture Correction and Health Monitoring for Yoga

Overview

The AI-Enabled Posture Correction and Health Monitoring for Yoga is an AI-powered yoga monitoring system designed to assist users in maintaining correct yoga postures and tracking vital health metrics. The system integrates sensors, AI models, and a web interface for real-time analysis and feedback.

Features

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• Posture Detection

AI model analyzes yoga poses using a camera.

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• Vital Monitoring

Uses a smart wristband with MAX30102 (heart rate & SpO2) and a temperature sensor.

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• Guided Yoga Sessions

Audio and visual feedback through an OLED screen and speakers.

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• Wireless Communication

ESP32 transmits data to a remote system.

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• Web App Integration

Displays real-time metrics and suggestions.

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Project Structure

SmartYogaMat/
│── data_collection.py    # Script for collecting sensor and video data
│── data_training.py      # Training the AI model for yoga posture recognition
│── inference.py         # Running inference to analyze poses and predict corrections
│── main.py             # Main control script for ESP32 and AI integration
│── client.cpp          # Client-side script for real-time data transmission
│── models/             # Pretrained and trained AI models
│── datasets/           # Collected dataset for training
│── web_app/            # Web interface for user interaction
│── requirements.txt    # Required dependencies
│── README.md           # Project documentation

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Installation

REQUIREMENTS:

HARDWARE:

• ESP32
• MAX30102 Sensor
• Temperature Sensor
• Pressure Sensors
• OLED Screen
• Speakers
• Webcam

SOFTWARE:

• Python 3.8+
• OpenCV
• TensorFlow/PyTorch
• Tkinter (for UI)

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Setup Instructions

1. Clone the repository:

   git clone https://github.com/yourusername/smart-yoga-mat.git
   cd smart-yoga-mat

2. Install dependencies:

   pip install -r requirements.txt

3. Run the data collection script:

   python data_collection.py

4. Train the AI model:

   python data_training.py

5. Start real-time inference:

   python inference.py

6. Run the main system:

   python main.py