This project aims to pave the way for the development of IMU-based gait phase estimation by employing the state-of-the-art technology, in particular deep learning algorithms.
This repository consists of:
- "Design-models-from-scratch" directory, for those who would like to design these models on their own from scratch.
- "Employ-trained-models" directory, please check Employ_trained_models directory if you want to use and test the trained models.
Moreover, the project will grow itselft step-by-step, therefore more trained models will be presented in this repo in the future. At this moment, the first SmartGait model, "SmartGait_01" is already trained by using data from only two individuals, which is still not a completed trained model for production, however, it is a proof of our concept for using LSTM algorithm to estimate three main gait phases, foot-off, mid-swing, and foot-contact.
*) For this Repo the Python version 3.9.6 was used. Please download Python from: https://www.python.org/downloads/
Create a new virtual environment by choosing a Python interpreter and making a .\venv directory to hold it:
- python -m venv .\venv
- .\venv\Scripts\activate
- pip install -r requirements.txt
-) deactivate # don't exit until you're done with your project