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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

• Posture Detection

AI model analyzes yoga poses using a camera.

• Vital Monitoring

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

• Guided Yoga Sessions

Audio and visual feedback through an OLED screen and speakers.

• Wireless Communication

ESP32 transmits data to a remote system.

• Web App Integration

Displays real-time metrics and suggestions.

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

Installation

REQUIREMENTS:

HARDWARE:

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

SOFTWARE:

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

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