1,721,247 research outputs found
The role of the sEMG signal processing in the field of the Human Movement Analysis
No full textThe 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
Adaptive Amplitude Estimation of Myoelectric Surface Signals recorded during Dynamic Protocols
No full textThis work deals with the estimation of the envelope of surface myoelectric signals recorded during movement. A new approach is presented based on an adaptive iterative procedure which guarantees good repeatability of the results and standardization in the processing approaches. This technique can help in studying the physiological mechanism driving muscular force also during movement
Spectral analysis for non-stationary signals from mechanical measurements: A parametric approach
No full textNon-parametric time-frequency methods for spectral estimation are increasingly used in the analysis of non-stationary signals. However, neither have their performance and limits of application been completely investigated nor has a comparison with other methods, such as parametric ones, been clearly established. This paper deals with the analysis of nonstationary signals of interest in mechanics, and more specifically, the performance of some non-parametric methods widely used for this analysis will be discussed; an autoregressive time-varying method, improved with respect to the classical parametric implementation, will be presented and its potential in analysing signals coming from mechanical systems will be shown; the performance of parametric and non-parametric methods will be compared. (C) 1999 Academic Press
Extraction of the envelope from surface EMG signals
No full textThe envelope of a surface myoelectric signal has been historically related to the force exerted
by muscles during contraction. In fact, during isometric contractions, signal amplitude has
been shown to be linearly related to the force. This relationship is no longer valid when
myoelectric data are recorded during body movement.
In routine work, the envelope of the signal is extracted by means of a technique based on a
full-wave rectifier followed by an integrator (smoothing filter) giving rise to the so-called
Integrated ElectroMyography (IEMG). This technique presents some drawbacks that are
mainly related to the subjective choice of parameters and to the loss of adaptivity to signal
characteristics, which limit its use in dynamic protocols and affects the comparison of results
obtained by different experimenters.
New approaches are therefore needed. This paper presents a method which aims to improve
the quality of the estimation and the standardization of the results while, at the same time,
being suitable for signals recorded both in static and dynamic conditions.
The new approach is based on an adaptive iterative procedure which automatically sets and
dynamically changes (according to signal characteristics) the length of the smoothing filter
used for the estimation.
The estimation error is far lower than that given by classical estimators and approaches the
theoretical lower bound. Moreover, the automatic choice of filter length guarantees good
repeatability of the results and standardization in the processing approaches. This technique
can therefore help in analyzing myoelectric signals recorded during dynamic protocols, and
in studying the physiological mechanism driving muscular force during movement, and also
the evolution of muscular fatigue
Optimal rejection of artifacts in the processing of surface EMG signals for movement analysis
No full textPagina web del corso di Elaborazione Dati e Segnali Biomedici sul sito del Dipartimento di Elettronica Applicata
No full textIl sito web viene costantemente aggiornato con l'inserimento di materiale multimediale di utilità in ambito didattico per il corso di Elaborazione di Dati e Segnali Biomedici
An experimental analysis of noise generating structures in turbulent jet
No full textNoise-generating structures in turbulent-jet are educed from in-flow velocity and pressure measurements conditioned on far-field acoustic measurements. The anemometric measurements are performed inside a high Re jet flow both on the jet axis and close to the shear layer, for several distances from the nozzle (0 less than or equal tox/D less than or equal to 20) in an anechoic chamber. Experimental data are analyzed through a proper conditional averaging procedure. A triggering method based on the far-field pressure maxima is used to extract events from experimental time series to identify time signatures of velocity and in-flow pressure induced by the coherent structures responsible for the measured far-field noise. The resulting anemometric and acoustic averaged signals are analyzed and discussed in the frame of the properties and topology of the associated coherent structures
Efficient algorithm for fatigue monitoring from dynamic surface myoelectric signals using a complex covariance approach
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