TITLE:
The Influence of Window Length Analysis on the Time and Frequency Domain of Mechanomyographic and Electromyographic Signals of Submaximal Fatiguing Contractions
AUTHORS:
Guilherme Nogueira-Neto, Eduardo Scheeren, Eddy Krueger, Percy Nohama, Vera Lúcia S. N. Button
KEYWORDS:
Mechanomyography; Electromyography; Window Length Analysis; Local Muscle Fatigue
JOURNAL NAME:
Open Journal of Biophysics,
Vol.3 No.3,
July
12,
2013
ABSTRACT:
Mechanomyography (MMG) acquires the oscillatory waves of contracting
muscles. Electromyography (EMG) is a tool for monitoring muscle overall
electrical activity. During muscle contractions, both techniques can
investigate the changes that occur in the muscle properties. EMG and MMG
parameters have been used for detecting muscle fatigue with diverse test
protocols, sensors and filtering. Depending on the analysis window length
(WLA), monitoring physiological events could be compromised due to
imprecision in the determination of parameters. Therefore, this study investigated
the influence of WLA variation on different MMG and EMG parameters during
submaximal isometric contractions monitoring MMG and EMG parameters. Ten
male volunteers performed isometric contractions of elbow joint. Triaxial
accelerometer-based MMG sensor and EMG electrodes were positioned on the biceps
brachii muscle belly. Torque was monitored with a load cell. Volunteers
remained seated with hip and elbow joint at angles of 110° and 90°,
respectively. The protocol consisted in maintaining torque at 70% of maximum
voluntary contraction as long as they could. Parameter data of EMG and the
modulus of MMG were determined for four segments of the signal. Statistical
analysis consisted of analyses of variance and Fisher’s least square
differences post-hoc test. Also, Pearson’s correlation was calculated to
determine whether parameters that monitor similar physiological events would
have strong correlation. The modulus of MMG mean power frequency (MPF) and the
number of crossings in the baseline could detect changes between fresh and
fatigued muscle with 1.0 s WLA. MPF and the skewness of the spectrum (μ3), parameters related to the
compression of the spectrum, behaved differently when monitored with a triaxial
MMG sensor. The EMG results show that for the 1.0 s and 2.0 s WLAs have
normalized RMS difference with fatigued muscle and that there was strong correlation
between parameters of different domains.