1,721,339 research outputs found
Amplitude indicators and spatial aliasing in high density surface electromyography recordings
No full texttAverage Rectified Value (ARV) and Root Mean Square (RMS) are amplitude indicators commonly usedin the field of EMG either in time or space. These two indicators are compared (a) analytically for a onedimensional sinusoid, sum of sinusoids, two dimensional sinusoids, and (b) numerically by simulating ahigh density detection system, sampling in space the distribution of propagating surface action potentialsgenerated by a muscle motor unit (MU). For any signal sampled above the Nyquist frequency the esti-mated RMS does not depend on the sampling rate while the estimated ARV does. The surface potentialis often sampled in space below the Nyquist frequency, by high density surface EMG detection systems(HDsEMG), generating aliasing in space. For point-like electrodes, the lowest spatial sampling frequencycorresponding to the largest inter-electrode distance (IED), which avoids spatial aliasing for a simulatedMU action potential, is 100 samples/m (IED = 10 mm). Therefore, IEDs below this value are recommendedfor measurements of EMG image features. From the theoretical point of view, the spatial RMS of sEMGimages is more robust than the ARV with respect to the IED and should be preferre
Motor units in cranial and caudal regions of the upper trapezius muscle have different discharge rates during brief static contractions
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Spectral variables do not necessarily reflect histological types of recruited motor units
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Raccomandazioni europee per l'elettromiografia di superficie: I risultati del Progetto SENIAM
No full textSISTEMA DI COLLEGAMENTO RIMUOVIBILE PER MATRICI DI ELETTRODII CUTANEI PER IL PRELIEVO DI SEGNALI BIOELETTRICI
No full textSurface Electromyography: Physiology, engineering, and applications
No full textReflects on developments in noninvasive electromyography, and includes advances and applications in signal detection, processing and interpretation. Addresses EMG imaging technology together with the issue of decomposition of surface EMG Includes advanced single and multi-channel techniques for information extraction from surface EMG signals Presents the analysis and information extraction of surface EMG at various scales, from motor units to the concept of muscle synergies
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