The role of surface ElectroMyoGraphy in human movement analysis is outlined by using a novel view. As reported in the most recent contributions appeared in the literature sEMG can be used extensively to assess the muscular synergies adopted by the Central Nervous System to control motor tasks. Muscular patterns revealed in agonist, antagonist and synergist muscles give insights on motor control through the use of parameters such as amplitude, timing and spectral characteristics. Modifications of these parameters reveal motor strategies that are implemented by modulating the motor units recruitment process. Recruitment and synchronization, that are further peripheral signs of central mechanisms, can then be assessed by properly processing sEMG signals. These new findings move the use of sEMG signals from the description of the movement to the inferential study about motor learning (re-learning), adaptation and control. Some technical issues on sEMG recording and processing need to be overcome and extensively assessed in order to interpret correctly the information extracted from signals. Several interesting future scenarios for sEMG use are outlined in this paper. If these preliminary proposals will have a future sEMG could be used to propose a new generation of Brain Neural Controlled Inter faces where the Neural contribution, to be interpreted as the motor neural command, will give inferences about the Brain contribution, and will allow to open new scenarios in the assistive technology field.

Conforto, S. (2009). The role of the sEMG signal processing in the field of the Human Movement Analysis. In IFMBE Proceedings (pp.523-526) [10.1007/978-3-642-03889-1-140 1].

The role of the sEMG signal processing in the field of the Human Movement Analysis

CONFORTO, SILVIA
2009

Abstract

The role of surface ElectroMyoGraphy in human movement analysis is outlined by using a novel view. As reported in the most recent contributions appeared in the literature sEMG can be used extensively to assess the muscular synergies adopted by the Central Nervous System to control motor tasks. Muscular patterns revealed in agonist, antagonist and synergist muscles give insights on motor control through the use of parameters such as amplitude, timing and spectral characteristics. Modifications of these parameters reveal motor strategies that are implemented by modulating the motor units recruitment process. Recruitment and synchronization, that are further peripheral signs of central mechanisms, can then be assessed by properly processing sEMG signals. These new findings move the use of sEMG signals from the description of the movement to the inferential study about motor learning (re-learning), adaptation and control. Some technical issues on sEMG recording and processing need to be overcome and extensively assessed in order to interpret correctly the information extracted from signals. Several interesting future scenarios for sEMG use are outlined in this paper. If these preliminary proposals will have a future sEMG could be used to propose a new generation of Brain Neural Controlled Inter faces where the Neural contribution, to be interpreted as the motor neural command, will give inferences about the Brain contribution, and will allow to open new scenarios in the assistive technology field.
Conforto, S. (2009). The role of the sEMG signal processing in the field of the Human Movement Analysis. In IFMBE Proceedings (pp.523-526) [10.1007/978-3-642-03889-1-140 1].
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11590/139656
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