4.6 Review

Fundamental Concepts of Bipolar and High-Density Surface EMG Understanding and Teaching for Clinical, Occupational, and Sport Applications: Origin, Detection, and Main Errors

Journal

SENSORS
Volume 22, Issue 11, Pages -

Publisher

MDPI
DOI: 10.3390/s22114150

Keywords

surface electromyography; surface EMG signal; high-density surface EMG; teaching; electrodes; crosstalk; volume conductor; conduction velocity; modeling

Funding

  1. European Union [846679]
  2. Marie Curie Actions (MSCA) [846679] Funding Source: Marie Curie Actions (MSCA)

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Surface electromyography (sEMG) has been extensively researched, but its clinical applications are limited. This study provides teaching tools using analogies and simulations, such as physical and mathematical models, to explain sEMG detection with electrode pairs and grids. The study summarizes the basic mechanisms of sEMG generation and illustrates the features of the sensing system through examples. It also discusses the various applications of sEMG in different fields.
Surface electromyography (sEMG) has been the subject of thousands of scientific articles, but many barriers limit its clinical applications. Previous work has indicated that the lack of time, competence, training, and teaching is the main barrier to the clinical application of sEMG. This work follows up and presents a number of analogies, metaphors, and simulations using physical and mathematical models that provide tools for teaching sEMG detection by means of electrode pairs (1D signals) and electrode grids (2D and 3D signals). The basic mechanisms of sEMG generation are summarized and the features of the sensing system (electrode location, size, interelectrode distance, crosstalk, etc.) are illustrated (mostly by animations) with examples that teachers can use. The most common, as well as some potential, applications are illustrated in the areas of signal presentation, gait analysis, the optimal injection of botulinum toxin, neurorehabilitation, ergonomics, obstetrics, occupational medicine, and sport sciences. The work is primarily focused on correct sEMG detection and on crosstalk. Issues related to the clinical transfer of innovations are also discussed, as well as the need for training new clinical and/or technical operators in the field of sEMG.

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