*Eargait* provides a set of algorithms and functions to process IMU data recorded with ear-worn IMU sensors and to estimate characteristic gait parameters.
EarGait provides a set of algorithms and functions to process IMU data recorded with ear-worn IMU sensors and to estimate characteristic gait parameters.
Easily install eargait via pip:
pip install eargait
or add it to your project with poetry:
poetry add eargait
Newest version 1.2.0 should be installed.
EarGait only supports Python 3.8 and newer. First, install a compatible version of Python.
We recommend installing the packages in a virtual environment (e.g. conda/Anaconda/miniconda).
For more information regarding Anaconda, please visit Anaconda.com.
If you want to install the packages directly on the local python version, directly go to Install Packages
If you are familiar with virtual environments you can ``also use any other type of virtual environment. Furthermore, you can also directly install the python packages on the local python version, however, we would not recommend doing so.
In PyCharm
See documentation.
Shell/Terminal
First, verify that you have a working conda installation. Open a terminal/shell and type
conda env list
If an error message similar to the one below is displayed, you probably do not have a working conda version installed.
conda: command not found
In the shell/terminal:
conda create --no-default-packages -n gait_analysis python=3.8
gait_analysis is the name of the virtual environment. This environment can now also be included in PyCharm,
as described See here
by using the existing environment option.
To check, whether the virtual environment has been created successfully, run again:
conda env list
The environment gait_analysis should now be displayed.
Activate conda environment and install packages (see below).
conda activate gait_analysis
For more help: Conda Documentation
If you are using the conda environment, activate environment (in shell/terminal) (see above).
Update pip and install eargait.
pip install --upgrade pip
pip install eargait
To check whether the installation was successful, run the following line directly after installing eargait in the same shell/terminal:
python examples/check_installation/check_installation.py
Should return: Installation was successful!
Documentation, User Guide, Coordinate Systems
We are using poetry to manage dependencies and poethepoet to run and manage dev tasks.
To set up the dev environment including the required dependencies for using EarGait run the following commands:
git clone https://github.com/mad-lab-fau/eargait
cd eargait
poetry install
Afterwards you can start to develop and change things. If you want to run tests, format your code, build the docs, ..., you can run one of the following poethepoet commands
CONFIGURED TASKS
format
lint Lint all files with Prospector.
check Check all potential format and linting issues.
test Run Pytest with coverage.
docs Build the html docs using Sphinx.
bump_version
by calling
poetry run poe <command name>
If you use Eargait in your work, please report the version you used in the text. Additionally, please also cite the corresponding paper:
[1] Seifer et al., "EarGait: estimation of temporal gait parameters from hearing aid
integrated inertial sensors." Sensors 23(14), 2023. https://doi.org/10.3390/s23146565.
[2] PREPRINT Seifer et al., (2023). Step length and gait speed estimation using a hearing aid
integrated accelerometer: A comparison of different algorithms.
Links:
[1] Seifer et al., (2023), Temporal Parameter Paper
[2] Seifer et al., (2023); Spatial Parameter Paper --> PREPRINT
EarGait is part of a research project from the Machine Learning and Data Analytics Lab, Friedrich-Alexander Universität Erlangen-Nürnberg. The authors thank WS Audiology, Erlangen, Germany and Lynge, Denmark for funding the work and their support which made this contribution possible.
The entire development is managed via GitHub. If you run into any issues, want to discuss certain decisions, want to contribute features or feature requests, just reach out to us by opening a new issue.
FAQs
*Eargait* provides a set of algorithms and functions to process IMU data recorded with ear-worn IMU sensors and to estimate characteristic gait parameters.
We found that eargait demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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