Surface electromyography (EMG) is a noninvasive technique that has the potential to provide information on how the nervous system controls movement. Nevertheless, conventional EMG methods with low spatial sampling resolution do not provide the necessary level of detail to study motor behavior. During the last decade, the emergence of high-density surface EMG (HDsEMG) systems has enabled a more detailed analysis of the firing patterns of alpha motoneurons to the muscle. Access to this information has improved our understanding of the neural mechanisms responsible for the control and generation of muscle force. This chapter will focus on the recording of HDsEMG signals and the processing techniques enabling the identification of motor unit firings from surface EMG recordings by employing HDsEMG.

Neuromuscular Function: High-Density Surface Electromyography

Martinez-Valdes E.;Negro F.
2023-01-01

Abstract

Surface electromyography (EMG) is a noninvasive technique that has the potential to provide information on how the nervous system controls movement. Nevertheless, conventional EMG methods with low spatial sampling resolution do not provide the necessary level of detail to study motor behavior. During the last decade, the emergence of high-density surface EMG (HDsEMG) systems has enabled a more detailed analysis of the firing patterns of alpha motoneurons to the muscle. Access to this information has improved our understanding of the neural mechanisms responsible for the control and generation of muscle force. This chapter will focus on the recording of HDsEMG signals and the processing techniques enabling the identification of motor unit firings from surface EMG recordings by employing HDsEMG.
2023
Altre Istituz. pubb. estere
Neuromethods
Inglese
204
105
123
19
978-1-0716-3314-4
978-1-0716-3315-1
Humana Press Inc.
Blind source separation; Decomposition; Electromyography; High-density surface electromyography; Motor neuron; Motor unit
no
Not applicable
2 Contributo in Volume::2.1 Contributo in volume (Capitolo o Saggio)
2
268
none
Martinez-Valdes, E.; Negro, F.
info:eu-repo/semantics/bookPart
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11379/590400
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