This project utilizes an Inertial Measurement Unit (IMU) sensor to capture real-time movement data of a person or object to which the IMU is attached. The collected data is then processed and visualized in both Python and MATLAB, creating a 3D model of the movement.
The project is designed for applications in motion analysis, gait analysis, fitness tracking, and more.
- Real-time data capture from the IMU sensor.
- 3D visualization of the movement trajectory.
- Python and MATLAB implementations for data processing and visualization.
- Customizable for various IMU sensors and tracking scenarios.
- IMU sensor (e.g., MPU6050, MPU9250, etc.)
- Microcontroller (e.g., Arduino, Raspberry Pi) for interfacing with the IMU.
- Attachments and mounting hardware for securing the IMU to the subject or object.
- Computer with USB connection for data transfer (if using microcontroller).
- Power source for the IMU and microcontroller.
- Python (for Python implementation)
- MATLAB (for MATLAB implementation)
- IMU sensor driver/library for data acquisition
- Appropriate libraries for data visualization (e.g., matplotlib, numpy, scipy, MATLAB plotting tools)
- Clone this repository to your local machine using
git clone. - Install the necessary software components and libraries as mentioned in the project's specific Python and MATLAB files.
- Connect the IMU sensor to the microcontroller and the subject or object whose movement you want to track.
- Run the Python or MATLAB script to begin data capture and visualization.
- Ensure the IMU sensor is correctly attached and positioned.
- Run the Python or MATLAB script to start data capture.
- Visualize the real-time movement trajectory in 3D.
- Customize the implementation to suit your specific tracking and visualization needs.