Abstract
ObjectiveThis work compares two known and one novel techniques for the detection of surface EMG (sEMG) quasi-periodic burst-like signals and the estimation of their frequency. The novel method (ES) is based on the spectral analysis of the envelope signal, the other two methods use a fixed (FT) or automatically selected optimal threshold (OT). MethodsThe methods are compared using both simulated signals and samples of High Density sEMG experimental signals collected using electrode arrays applied to the erector spinae muscles of violinists. ResultsThe ES method does not require thresholds. It detects presence/absence of bursts and their frequency, even in cases of a few missing bursts. It does not provide their duration. The FT method requires the selection of a fixed threshold value, estimates burst duration but is applicable only if bursts are present. The OT method identifies an optimal threshold, estimates burst duration but behaves irregularly when bursts are small or absent. ConclusionsThe ES method provides the estimates closest to those of an expert human counter and is not sensitive to amplitude fluctuations. It is suitable when the general bursts periodicity is of interest even if some bursts may be missing. The FT and OT methods are sensitive to amplitude fluctuations and identify random threshold crossings as bursts even when burst activity is absent. SignificancePostural muscles are often activated in a burst-like fashion. The proposed ES method identifies presence/absence of bursts and their frequency, which is important for studying the neurophysiological mechanism generating them.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.