pyemgpipeline

pyemgpipeline: A Python package for electromyography processing - Published in JOSS (2022)

https://github.com/aalhossary/pyemgpipeline

Science Score: 93.0%

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    Found 1 DOI reference(s) in JOSS metadata
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    Published in Journal of Open Source Software

Scientific Fields

Mathematics Computer Science - 40% confidence
Last synced: 6 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: aalhossary
  • License: gpl-3.0
  • Language: Python
  • Default Branch: master
  • Size: 16.6 MB
Statistics
  • Stars: 11
  • Watchers: 3
  • Forks: 4
  • Open Issues: 0
  • Releases: 1
Created over 4 years ago · Last pushed almost 4 years ago
Metadata Files
Readme License

README.md

EMG Signal Processing Pipeline

pyemgpipeline is an electromyography (EMG) signal processing pipeline package.

This package implements internationally accepted EMG processing conventions and provides a high-level interface for ensuring user adherence to those conventions, in terms of (1) processing parameter values, (2) processing steps, and (3) processing step order.

The processing steps included in the package are DC offset removal, bandpass filtering, full wave rectification, linear envelope, end frame cutting, amplitude normalization, and segmentation.

Scope

This package defines the processing pipeline for both surface EMG and intramuscular EMG but not for high density EMG. The EMG recording requires that the minimum sample rate be at least twice the highest cutoff frequency of the bandpass filter based on the Nyquist theorem.

Overview

In pyemgpipeline, class DataProcessingManager in module wrappers is designed as the main wrapper for high-level, guided processing, and users are encouraged to use it to adhere to accepted EMG processing conventions. The other classes, methods, and functions are considered as lower level processing options.

The package is organized in modules processors, wrappers, and plots.

Module processors includes the base class BaseProcessor of all signal processors and seven classes for different processing steps: DCOffsetRemover, BandpassFilter, FullWaveRectifier, LinearEnvelope, EndFrameCutter, AmplitudeNormalizer, and Segmenter.

Module wrappers includes three wrapper classes to facilitate the signal processing by integrating data and individual processors. Class EMGMeasurement works for data of a single trial, class EMGMeasurementCollection works for data of multiple trials, and class DataProcessingManager is the high-level, guided processing wrapper with EMG processing conventions.

Module plots includes the function plot_emg to plot EMG signals on matplotlib figures and the class EMGPlotParams to manage the plot-related parameters.

Documentation

The documentation describes how to use this package, including package installation, quick start, examples explaining the breadth of the package’s functionality, and API reference.

Community Guidelines

For contribution, please clone the repository, make changes, and create a pull request.

For reporting any issues, please use github issues.

For support, please contact the authors via their emails or github issues.

Citation

If you use this package in your project, please cite this work.

Owner

  • Name: Amr ALHOSSARY
  • Login: aalhossary
  • Kind: user
  • Location: United States
  • Company: Wesleyan University

Postdoctoral research fellow

JOSS Publication

pyemgpipeline: A Python package for electromyography processing
Published
April 12, 2022
Volume 7, Issue 72, Page 4156
Authors
Tsung-Lin Wu ORCID
Nanyang Technological University, School of Mechanical & Aerospace Engineering
Amr A. Alhossary ORCID
Nanyang Technological University, Rehabilitation Research Institute of Singapore
Todd C. Pataky ORCID
Kyoto University, Department of Human Health Sciences
Wei Tech Ang ORCID
Nanyang Technological University, School of Mechanical & Aerospace Engineering, Nanyang Technological University, Rehabilitation Research Institute of Singapore
Cyril J. Donnelly ORCID
Nanyang Technological University, Rehabilitation Research Institute of Singapore
Editor
Øystein Sørensen ORCID
Tags
electromyography EMG processing

GitHub Events

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  • Watch event: 1
  • Fork event: 1
Last Year
  • Watch event: 1
  • Fork event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 71
  • Total Committers: 2
  • Avg Commits per committer: 35.5
  • Development Distribution Score (DDS): 0.113
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
tlwu t****8@g****m 63
Amr ALHOSSARY a****y@h****m 8

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 4
  • Total pull requests: 0
  • Average time to close issues: 13 days
  • Average time to close pull requests: N/A
  • Total issue authors: 2
  • Total pull request authors: 0
  • Average comments per issue: 2.25
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • osorensen (3)
  • tuliofalmeida (1)
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Top Labels
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Packages

  • Total packages: 1
  • Total downloads:
    • pypi 138 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 3
  • Total maintainers: 1
pypi.org: pyemgpipeline

EMG signal processing pipeline

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 138 Last month
Rankings
Dependent packages count: 10.0%
Downloads: 15.5%
Average: 16.5%
Forks count: 16.8%
Stargazers count: 18.5%
Dependent repos count: 21.7%
Maintainers (1)
Last synced: 6 months ago

Dependencies

setup.py pypi
  • matplotlib *
  • numpy *
  • scipy *