IMU-Fundamentals

Code repository outlining basic concepts related to using inertial measurement units (IMUs) for human motion analysis.

Running in Python

Environment setup

Python users must setup an appropriate environment to run the IMU-Fundamentals notebook. This can be run in any IDE that supports Jupyter notebooks (such as Jupyter Notebook, JupyterLab, VS Code, etc.) after cloning the repository and changing your directory accordingly.

1. Create environment: conda env create -f environment.yml
2. Activate environment: conda activate IMU_Funds
3. Open IMU_Fundamentals.ipynb and run all cells in order

Running through the tutorial

Users can find the tutorial within IMU_Fundamentals.ipynb. All cells should be run in order. The table2zoo_data/ folder will be created automatically when you run the cells. All functions that are used throughout the tutorial can be inspected within their respective .py files within the utils/ folder.

Project Structure

IMU-Fundamentals/
├── IMU_Fundamentals.ipynb    # Main tutorial notebook
├── environment.yml            # Conda environment file
├── README.md                  # This file
└── utils/                     # Utility functions

Additional Setup

This notebook uses an external IMU visualization tool. Before running the visualization cells, you need to clone the imu-visualization repository:

git clone https://github.com/jlwry/imu-visualization

Once cloned, update the visualizer_path variable in the visualization cell to point to the location where you cloned the repository. For example:

visualizer_path = '/path/to/your/imu-visualization'
visualize(data_path, visualizer_path)

Make sure the path points to the directory containing the vis_3D_rot_scikit_V4.py file.

Requirements

• Python 3.11+
• Conda (for environment management)

Author & License

Joshua Lowery - MSc Biomechanics Student @ McGill Univeristy's MOTION Laboratory.

GPL-3.0 license