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Articles in PresS, published online ahead of print August 9, 2002
J Appl Physiol, 10.1152/jap.00314.2002
Submitted on April 10, 2002
Accepted on August 8, 2002
1 Dip. di Elettronica, Centro di Bioingegneria, Politecnico di Torino, Torino, Italy
2 Dip. Fisiologia Umana e Farmacologia, Universita di Roma "La Sapienza", Roma, Italy; Scuola di Medicina dello Sport, Universita di Roma "La Sapienza", Roma, Italy
3 Istituto Universitario di Scienze Motorie, Roma, Italy
4 Dip. INFOCOM, Universita di Roma "La Sapienza", Roma, Italy; Centro Interdipartimentale Sistemi Biomedici, Universita degli Studi, Roma, Italy
* To whom correspondence should be addressed. E-mail: farina{at}athena.polito.it.
Amplitude and frequency content of the surface electromyographic (EMG) signal reflect central and peripheral modifications of the neuromuscular system. Classic surface EMG spectral variables applied to assess muscle functions are the centroid and median power spectral frequencies (MNF and MDF). More recently, non linear tools have been introduced to analyze the surface EMG; among them the recurrence quantification analysis (RQA) was shown to be particularly promising for the detection of changes of the muscle status. The purpose of this work was to analyze the effect of motor unit (MU) short term synchronization and conduction velocity (CV) on EMG spectral variables and two variables extracted by RQA, the percentage of recurrence (%REC) and of determinism (%DET). The study was performed on the basis of a simulation model which allowed changing the degree of synchronization and mean CV of a number of MUs and of an experimental investigation of the properties of the surface EMG signals detected during high force level isometric fatiguing contractions of the biceps brachii muscle. Simulations and experimental results were largely in agreement and show that 1) spectral variables, %REC, and %DET are influenced by CV and degree of synchronization, 2) spectral variables are highly correlated with %DET (R=-0.95 in the simulations, R=-0.78 and R=-0.75 for the initial values and normalized slopes, respectively, in the experimental signals) and, thus, the information they provide on muscle properties is basically the same, 3) variations of %DET and %REC in response to changes of muscle properties are significantly larger than the variations of spectral variables. This study validates RQA as a means for fatigue assessment with potential advantages (such as the higher sensitivity to changes of muscle status) with respect to the classic spectral analysis.
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