SPECIAL COMMUNICATIONS: Letters to the Editor-in-Chief
We read with great interest the interesting article by Hendrix et al. (3) regarding whether the mathematical model for estimating the EMG fatigue threshold (EMGFT) during cycle ergometry was applicable to isometric leg extensions.
The EMGFT has been widely studied using pedaling tests (2,6,7), and it has been shown to be a useful tool in assessing the fitness level/muscle performance (1,2,6,7). This method carries the advantage that it does not require submaximal exercise bouts to be performed until exhaustion. Because of this, EMGFT is very useful for patients who are unable to tolerate maximal effort. However, in the present study (3), and in the literature in general, the authors did not apply any criteria to establish the precision of their EMGFT determination and did not report the standard error (SE) of their EMGFT values. Nevertheless, EMGFT should be considered as a valid tool to assess muscle function/fitness level (and to monitor changes in response to training/rehabilitation programs) only if the values are determined in a way that small changes over time or between subjects can be detected. Although the precision of EMGFT depends on the linear fit used to model the relationship between the force level and slope coefficient, Hendrix et al. (3) determined EMGFT by using a coefficient of determination R2 < 0.85 (6 cases of 22), which certainly resulted in a high SE of the y-intercept (i.e., EMGFT). For instance, from the Table 2, we calculated a high SE of EMGFT for subject 3 (±15.5% of MVC, for rectus femoris). That suggests that EMGFT values reported in this article (and in the literature in general) would not be always precise. In fact, in a recent study (4), we chose to validate the EMGFT determination from isometric elbow flexion only for significant positive linear regressions with R2 > 0.85 and with SE of the y-intercept (i.e., EMGFT) less than 5% of MVC. By applying these stringent criteria, it was noted that EMGFT could only be determined for one muscle (the long head of biceps brachii) for just three of the eight subjects.
The inability to detect an EMGFT precisely in all the subjects could be explained by various factors, such as
- a nonlinear relationship between the increase in EMG amplitude and time,
- putative compensations between muscles, and
- nonhomogeneous distribution of EMG activity within a muscle.
By using alternate techniques, however, some of these limitations could be avoided. First, to circumvent the limitation associated with the potential nonlinear relationship between the increase in EMG amplitude and time, Merletti et al. (5) suggested the use of the "area ratio." This "area ratio" index is regression-free, dimensionless, and it is little affected by experimental point fluctuations. Second, because compensations between muscles can interfere with the determination of a precise EMGFT, ideally, simple tasks involving one main muscle should be used for the experimental protocol. Third, because the distribution of EMG activity could be nonhomogeneous (8), we propose to record EMG with a multichannel amplifier, which would permit the investigator to obtain a map of activity level and thus to choose, a posteriori, the best site to determine the EMGFT.
1. deVries HA, Moritani T, Nagata A, Magnussen K. The relation between critical power and neuromuscular fatigue as estimated from electromyographic data. Ergonomics
2. Graef JL, Smith AE, Kendall KL, et al. The relationships among endurance performance measures as estimated from V˙O2peak
, ventilatory threshold, and electromyographic fatigue threshold: a relationship design. Dyn Med
3. Hendrix CR, Housh TJ, Johnson GO, et al. Comparison of critical force to EMG fatigue thresholds during isometric leg extension. Med Sci Sports Exerc
4. Hug F, Nordez A, Guevel A. Can the electromyographic fatigue threshold be determined from superficial elbow flexor muscles during an isometric single-joint task? Eur J Appl Physiol
5. Merletti R, Lo Conte LR, Orizio C. Indices of muscle fatigue. J Electromyogr Kinesiol
6. Moritani T, Takaishi T, Matsumoto T. Determination of maximal power output at neuromuscular fatigue threshold. J Appl Physiol
7. Smith AE, Moon JR, Kendall KL, et al. The effects of β-alanine supplementation and high-intensity interval training on neuromuscular fatigue and muscle function. Eur J Appl Physiol
8. Zijdewind I, Kernell D, Kukulka CG. Spatial differences in fatigue-associated electromyographic behaviour of the human first dorsal interosseus muscle. J Physiol