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The aims of the present study were (1) to investigate the differences in median frequency characteristics between back and hip muscles of healthy subjects during a Biering-Sørensen test, (2) to determine if the Biering-Sørensen test is a valid test for measuring back muscle fatigue, and (3) to standardise the Biering-Sørensen test by using objective movement analysis when defining endurance time, and compare this to the original method based on tactile feedback. Twenty healthy subjects participated in this experiment. The electromyographic activity of eight back and hip muscles was bilaterally measured. In addition three-dimensional data of the lumbar region were collected with an ultrasound movement analysis system. Median frequencies were computed from the EMG power spectra. Two methods of determining the endurance time of the Biering-Sørensen test yielded highly correlated but significantly different normalized median frequency slope values (NMF(slope)). Significant differences in NMF(slope) values between several back and hip muscles could be demonstrated. Low to moderate correlation coefficients were shown between NMF(slope) values and endurance time. Multiple stepwise linear regression analyses revealed that only NMF(slope) of the thoracic part of the iliocostalis lumborum muscle could significantly predict the test endurance time. The findings of the present study support the validity of the Biering-Sørensen test for measuring back muscle fatigue.

The present study aimed at assessing the test-retest reliability of wavelet - and Fourier derived (instantaneous) median frequencies of surface electromyographic (EMG) measurements of back and hip muscles during isometric back extensions. Twenty healthy subjects (10 males and 10 females) performed a modified Biering-Sørensen test on two separate days, with a 1-week interval between the two tests. Surface EMG measurements were bilaterally performed from the latissimus dorsi, the thoracic and lumbar parts of the longissimus thoracis, the thoracic and lumbar parts of the iliocostalis lumborum, the multifidus, the gluteus maximus and the biceps femoris. In addition, three-dimensional kinematic data were recorded of the subjects' lumbar vertebrae. The (instantaneous) median frequencies were calculated from the EMG signals using continuous wavelet (IMDF) - and short-time Fourier transforms (MDF). Linear regressions performed on the IMDF and MDF data as a function of time yielded slopes (IMDF(slope) and MDF(slope)) and intercepts (IMDF(init) and MDF(init)) of the regression lines. Test-retest reliability was assessed on the normalized slopes and intercept parameters by means of intraclass correlation coefficients (ICC) and standard errors of measurements expressed as percentages of the mean values (% SEM). The results of IMDF(slope) and MDF(slope) parameters indicated ICCs for back and hip muscles between .443 and .727 for IMDF(slope), values between .273 and .734 for MDF(slope), % SEM between 7.6% and 58.9% for IMDF(slope) and % SEM between 8.2% and 25.3% for MDF(slope), respectively. The ICCs for IMDF(init) and MDF(init) parameters varied between .376 and .907 for IMDF(init) and between .383 and .883 for MDF(init), and % SEM ranged from 2.7% to 6.3% for IMDF(init) and from 2.6% to 4.7% for MDF(init), respectively. These results indicate that both wavelet - and Fourier based (instantaneous) median frequency parameters generally are reliable in the analysis of back and hip muscle fatigue during a modified Biering-Sørensen test.

The aims of the current study were to examine the stationarities of surface electromyographic (EMG) signals obtained from eight bilateral back and hip muscles during a modified Biering-Sørensen test, and to investigate whether short-time Fourier (STFT) and continuous wavelet transforms (CWT) provided similar information with regard to EMG spectral parameters in the analysis of localized muscle fatigue. Twenty healthy subjects participated in the study after giving their informed consent. Reverse arrangement tests showed that 91.6% of the EMG signal epochs demonstrated no significant trends (all p>0.05), meaning 91.6% of the EMG signal epochs could be considered as stationary signals. Pearson correlation coefficients showed that STFT and CWT in general provide similar information with respect to the EMG spectral variables during isometric back extensions, and as a consequence STFT can still be used.

Abstract: Wavelets are used for the processing of signals that are non-stationary and time varying. The electromyogram (EMG) contains transient signals related to muscle activity. Wavelet coefficients are proposed as features for identifying muscle fatigue. By observing the approximation coefficients it is shown that their amplitude follows closely the muscle fatigue development. The proposed method for detecting fatigue is automated by using neural networks. The self-organizing map (SOM) has been used to visualize the variation of the approximation wavelet coefficients and aid the detection of muscle fatigue. The results show that a 2D SOM separates EMG signatures from fresh and fatigued muscles, thus providing a visualization of the onset of fatigue over time. The map is able to detect if muscles have recovered temporarily. The system is adaptable to different subjects and conditions since the techniques used are not subject or workload regime specific. [Copyright &y& Elsevier]