2005
DOI: 10.1016/j.jelekin.2004.08.008
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An EMG fractal indicator having different sensitivities to changes in force and muscle fatigue during voluntary static muscle contractions

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Cited by 57 publications
(46 citation statements)
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“…Other research found that maximal elbow angles would result in high RMS values in isometric contractions [10]. In addition, changes in the elbow angle (for isometric contractions) gives a shift in the median frequencies of the EMG signal at fatigue occurrence [5]. The findings in these previous studies, as well as the performance of the different feature extraction methods in this study, showed that these parameters are useful in finding the optimal angle.…”
Section: Discussionsupporting
confidence: 66%
See 1 more Smart Citation
“…Other research found that maximal elbow angles would result in high RMS values in isometric contractions [10]. In addition, changes in the elbow angle (for isometric contractions) gives a shift in the median frequencies of the EMG signal at fatigue occurrence [5]. The findings in these previous studies, as well as the performance of the different feature extraction methods in this study, showed that these parameters are useful in finding the optimal angle.…”
Section: Discussionsupporting
confidence: 66%
“…• in the biceps brachii to analyse fluctuations, which indicate fatigue in the sEMG signal, based on a shift in the median frequencies [5]. In muscle fatigue research a goniometer is often used together with other signal detection methods, yielding additional useful information about the fatiguing muscle.…”
Section: Introductionmentioning
confidence: 99%
“…These signals are recorded and then processed with a power spectrum analysis. The median frequency (MF) is defined as the frequency at which the spectrum is divided into two equal parts [3]. The typical MF range is from 70 to 120 Hz [4], which corresponds to a time scale of 10 to 20 ms.…”
Section: Introductionmentioning
confidence: 99%
“…Another study found that amplitude-related characteristics of motor units can help to avoid misleading interpretations of sEMG changes [11]. Ravier et al pursued a different approach and fitted the sEMG frequency spectrum to P( f ) 1/f α behavior, where P is the power of the signal, f is the frequency, and α > 0 is an exponent [3]. Such behavior was originally derived for "self-organized" systems such as avalanches [12].…”
Section: Introductionmentioning
confidence: 99%
“…Some others recent works [1,2,5,8,12] present a fractal structure of the muscle, which consolidate the approach based on the use of non integer (or fractal) model to characterize its dynamic behaviour. A fractional structure model, due to its infinite dimension nature, is particularly adapted to model complex systems with few parameters, and to obtain real time exploitable model: muscle complexity can be described thanks to fractional models, with a model containing a reduced number of parameters.…”
Section: Introductionmentioning
confidence: 98%