Frequency Parameters of the Myoelectric Signal as a Measure of Muscle Conduction Velocity

Abstract

Abstract-During a sustained muscle contraction, the lpectlUm of the myoelectric lignal is known to undergo compression as a function of time. Previous investigators have shown that the frequency compres sion is related to the decreasing conduction velocity of the muscle fi bers. It is proposed that the frequency compression may be tracked by obtaining a continuous estimate of a characteristic frequency of the spectrum, such as the mean and median, or the ratioof low-frequency components to high-frequency components of the speetrum. A theo retical analysis was performed to investigate the restrictions in estimat ing the three parameters, as well as their sensitivity to the conduction velocity. The ratio parameter was found to be mostsensitive to con duction velocity, but was the least reliable of the three. The median frequency was the least sensitive to noise. Therefore, from a theoretical point of view, the median frequency is the preferred parameter. A technique is described which determines an unbiased consistent esti mate of the median frequency. The technique may be readily imple mented in analog hardware.

Nonlinear surface EMG analysis to detect changes of motor unit conduction velocity and synchronization

“…It has been clearly established that the rate of change of spectral variables and conduction velocity (CV) during a sustained contraction is indicative of muscle fatigue (31) and may be correlated with MU type (39,43). It has also been shown, both theoretically (28,41) and experimentally (2), that, during fatiguing contractions, CV and mean (MNF) or median spectral frequency (MDF) of the surface EMG signal are highly correlated; MNF and MDF reflect mainly the CV changes of the active MUs. However, the comparison of the percent rate of CV and MNF and MDF decrease showed that, although being the main contribution to spectral compression, CV is not the only determinant of changes of the characteristic spectral frequencies.…”

“…In addition to the efforts devoted to the technical issue of estimating amplitude and spectral variables in a reliable way (12,32,41), many studies were focused, in the past, on the clarification of the relationships between these global variables and the underlying physical processes, to extract information of physiological interest from the global analysis of the surface EMG signal. It has been clearly established that the rate of change of spectral variables and conduction velocity (CV) during a sustained contraction is indicative of muscle fatigue (31) and may be correlated with MU type (39,43).…”

Chaos Based Quantitative Electro-Diagnostic Marker for Diagnosis of Myopathy, Neuropathy and Motor Neuron Disease

“…They observed the area of the multifractal spectrum of the SEMG signals to increase significantly during muscle fatigue. Thus they concluded that the area of the multifractal spectrum could then be used as an assessor of muscle fatigue which is more sensitive than the single characteristic frequency such as the median frequency (MDF) or mean frequency (MNF) of the power spectral density (PSD) which was a then popular method of estimating fatigue [86,87]. They also opined that the large area of SEMG multifractal singularity spectrum reflects the strengthened activity of the nervous system of the body in the process of muscle fatigue [86].…”

Análise da freqüência mediana do sinal eletromiográfico de indivíduos com lesão do ligamento cruzado anterior em exercícios isométricos de cadeia cinética aberta e fechada

“…Nonetheless, the SEMG presents other tolls that have been little explored in the literature that analyses individuals with ACL lesion as medium frequency (Fmed). The Fmed of the electromyographic signal is a variable that divides the power spectrum in two equal regions (20) , and can be used for physiological muscular fatigue (21) and type II fiber atrophy detection (22) with consequent variation in the velocity of conduction in the muscular fiber (23) .…”