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Extraction of the EPP Component from the Surface EMG
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Tutorial. Surface EMG detection, conditioning and pre-processing: Best practices.

R Merletti1, G L Cerone1

  • 1LISiN - Laboratory for Engineering of the Neuromuscular System, Department of Electronics and Telecommunications - Politecnico di Torino, Turin, Italy.

Journal of Electromyography and Kinesiology : Official Journal of the International Society of Electrophysiological Kinesiology
|August 9, 2020
PubMed
Summary
This summary is machine-generated.

This tutorial explains surface electromyography (sEMG) basics for non-engineers. It covers signal detection, properties, amplification, artifact reduction, filtering, and A/D conversion for muscle evaluation.

Keywords:
Artifact reductionElectrodesElectrode–skin impedanceElectromyographyInterference reductionKinesiologyNoise reductionPhysiotherapySignal conditioningTeachingTutorialsEMG acquisitionsEMG amplifiersEMG detection

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Science
  • Clinical Assessment

Background:

  • Surface electromyography (sEMG) is a valuable tool for muscle evaluation in clinical settings.
  • Non-engineers often require foundational knowledge for effective sEMG application.
  • Previous tutorials covered sEMG origin and electrode placement.

Purpose of the Study:

  • To explain fundamental concepts of sEMG signal detection, properties, and conditioning.
  • To provide practical guidelines for signal acquisition and analog-to-digital conversion.
  • To support non-engineers in utilizing sEMG for muscle assessment in various fields.

Main Methods:

  • Tutorial-based explanation of core sEMG concepts.
  • Discussion of signal detection parameters including electrodes and interfaces.
  • Explanation of amplifier characteristics, noise reduction, filtering, and A/D conversion.

Main Results:

  • Provides a clear understanding of basic sEMG signal properties (amplitude, bandwidth).
  • Details essential front-end amplifier parameters (input impedance, noise, CMRR).
  • Outlines techniques for interference and artifact reduction, crucial for accurate sEMG data.

Conclusions:

  • This tutorial equips non-engineers with essential knowledge for sEMG signal detection and conditioning.
  • Best practices for signal acquisition and A/D conversion are provided for clinical operators and engineers.
  • Establishes a foundation for subsequent tutorials on sEMG information extraction.