Skip to main content

Open-source analysis of High-Density EMG data

Project description

Welcome to openhdemg



Overview

openhdemg is a powerful toolbox for the analysis of HD-EMG recordings.

openhdemg is an open-source framework written in Python 3 with many functionalities specifically designed for the analysis of High-Density Electromyography (HD-EMG) recordings. Some of its main features are listed below, but there is much more to discover! For a full list of available functions, please refer to the API reference section at www.giacomovalli.com/openhdemg.

  1. Load decomposed HD-EMG files from various sources, such as .mat and .csv files. This allows to interface openhdemg with the commonly used softwares like OTBioLab+ or DEMUSE and potentially with any other software.
  2. Visualise your EMG or force/reference signal, as well as the motor units' firing times and their action potentials shape.
  3. Edit your file changing the reference signal offset, filtering noise, calculating differential derivations and removing unwanted motor units.
  4. Analyse motor units' recruitment/derecruitment thresholds, discharge rate, conduction velocity, action potentials amplitude and more...
  5. Remove duplicates between different files from the same recording session and analyse them together to increase the number of motor units'.
  6. Track motor units' across different recording sessions.
  7. Save the results of the analyses and the edited file.

Start immediately

If you already know how to use Python, that's the way to go! Otherwise, have a look at the tutorial explaining how to Setup your Python working environment.

openhdemg can be easily installed using pip:

pip install openhdemg

or conda:

conda install -c conda-forge openhdemg

If you want an overview of what you can do with the openhdemg library, have a look at the Quick Start section.

Good to know

In addition to the rich set of modules and functions presented in the API documentation, openhdemg offers also a practical graphical user interface (GUI) from which many tasks can be performed without writing a single line of code!

After installing the openhdemg package, the GUI can be simply accessed from the command line (check to be into the virtual environment) with:

python -m openhdemg.gui.openhdemg_gui

Once opened, it will look like this. It is cool, isn't it?

gui_preview

Why openhdemg

The openhdemg project was born in 2022 with the aim to provide the HD-EMG community with a free and open-source framework to analyse motor units' properties.

The field of EMG analysis in humans has always been characterized by a lack of available software for signal post-processing and analysis. This has forced users to code their own scripts, which can lead to problems when the scripts are not shared open-source. Why?

  • If different users use different scripts, the results can differ.
  • Any code can contain errors, if the code is not shared, the errors will never be known and them will repeat in the following analyses.
  • There is a significant difference between the methods presented in research papers and the practical implementation of a script. Reproducing a script solely based on written instructions can be challenging, making the reproducibility of a study unrealistic.
  • Anyone who doesn't code, will not be able to analyse the recordings.

In order to overcome these problems, we developed a fully transparent framework for the analysis of motor units' properties.

This project is intended for the users that already know the Python language, for those willing to learn it and even for those not interested in coding, thanks to a friendly graphical user interface (GUI).

Both the openhdemg project and its contributors adhere to the Open Science Principles and especially to the idea of public release of data and other scientific resources necessary for conducting honest research.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

openhdemg-0.1.0b2.tar.gz (11.9 MB view details)

Uploaded Source

Built Distribution

openhdemg-0.1.0b2-py3-none-any.whl (11.9 MB view details)

Uploaded Python 3

File details

Details for the file openhdemg-0.1.0b2.tar.gz.

File metadata

  • Download URL: openhdemg-0.1.0b2.tar.gz
  • Upload date:
  • Size: 11.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.7

File hashes

Hashes for openhdemg-0.1.0b2.tar.gz
Algorithm Hash digest
SHA256 71f0bfb7389d46629f046d034fa234620e3402b7daa61256cd01481ca83c3567
MD5 14b9f175594c97dc550ab4f093693a1a
BLAKE2b-256 76d03c2665a6fbfb2b29833685f35f3df3b3d8c86e4384b282739e6c38a41e52

See more details on using hashes here.

File details

Details for the file openhdemg-0.1.0b2-py3-none-any.whl.

File metadata

  • Download URL: openhdemg-0.1.0b2-py3-none-any.whl
  • Upload date:
  • Size: 11.9 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.7

File hashes

Hashes for openhdemg-0.1.0b2-py3-none-any.whl
Algorithm Hash digest
SHA256 94876f25b7c6ab2bb04177836ec6f70da4973b37cad83afd0741067fdc6bb364
MD5 ae46c4242f6fa6e2be6a2acb692fbd1e
BLAKE2b-256 5e85e0bcb4fc14e5bf87e510abdef5c8c1dc3099c46184ab3e3510b09abaca76

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page