High-Density surface Electromyography (HD-sEMG) is the most established technique for the non-invasive analysis of single motor unit (MU) activity in humans. It provides the possibility to study the central properties (e.g., discharge rate) of large populations of MUs by analysis of their firing pattern. Additionally, by spike-triggered averaging, peripheral properties such as MUs conduction velocity can be estimated over adjacent regions of the muscles and single MUs can be tracked across different recording sessions. In this tutorial, we guide the reader through the investigation of MUs properties from decomposed HD-sEMG recordings by providing both the theoretical knowledge and practical tools necessary to perform the analyses. The practical application of this tutorial is based on openhdemg, a free and open-source community-based framework for the automated analysis of MUs properties built on Python 3 and composed of different modules for HD-sEMG data handling, visualisation, editing, and analysis. openhdemg is interfaceable with most of the available recording software, equipment or decomposition techniques, and all the built-in functions are easily adaptable to different experimental needs. The framework also includes a graphical user interface which enables users with limited coding skills to perform a robust and reliable analysis of MUs properties without coding.

Tutorial: Analysis of central and peripheral motor unit properties from decomposed High-Density surface EMG signals with openhdemg

Valli G.
;
Casolo A.;De Vito G.
2024

Abstract

High-Density surface Electromyography (HD-sEMG) is the most established technique for the non-invasive analysis of single motor unit (MU) activity in humans. It provides the possibility to study the central properties (e.g., discharge rate) of large populations of MUs by analysis of their firing pattern. Additionally, by spike-triggered averaging, peripheral properties such as MUs conduction velocity can be estimated over adjacent regions of the muscles and single MUs can be tracked across different recording sessions. In this tutorial, we guide the reader through the investigation of MUs properties from decomposed HD-sEMG recordings by providing both the theoretical knowledge and practical tools necessary to perform the analyses. The practical application of this tutorial is based on openhdemg, a free and open-source community-based framework for the automated analysis of MUs properties built on Python 3 and composed of different modules for HD-sEMG data handling, visualisation, editing, and analysis. openhdemg is interfaceable with most of the available recording software, equipment or decomposition techniques, and all the built-in functions are easily adaptable to different experimental needs. The framework also includes a graphical user interface which enables users with limited coding skills to perform a robust and reliable analysis of MUs properties without coding.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3505841
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