Electromyography (EMG) involves the documentation of the electrical activity of muscle tissue and relaying it as a graphical representation or an audible signal. When muscles contract, the ensuing action potentials are transmitted from the brain to the motor unit, thereby causing the contraction of muscle fibers (Ertl, Kruse, & Tilp, 2016). Through EMG studies, researchers can quantify the extent of muscle activation. EMG techniques are classified as either invasive and noninvasive approaches. A fine wire or needle is inserted into muscle tissue to record muscle activation in invasive techniques (Lozano-García et al., 2015). Conversely, noninvasive EMG entails putting electrodes on the surface of the skin over the muscle being investigated (Malek & Coburn, 2012).
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The purpose of this review is to examine the concept of EMG fatigue threshold (EMGFT). The applications of EMG in the investigation of muscle fatigue are explained. Differences in EMGFT in large and small muscles are also explained.
EMG has amplitude and frequency domains (Altın & Er, 2016). The EMG amplitude quantifies the recruitment of the motor unit as well as its firing rate. These parameters are of immense importance when studying cycle ergometry. Conversely, the EMG frequency is thought to replicate the conduction speed of the muscle action potential. EMGFT was originally referred to as the physical working aptitude at the onset of fatigue. However, after several investigations on the issue, the EMGFT was defined as the greatest exercise force that can be sustained indeterminately with no substantial rise in gradient when EMG amplitude is plotted against time (Mahmutović et al., 2016).
The concept of EMGFT has been demonstrated in large muscles by Morse et al. (2016). These authors demonstrated that the consumption of caffeine improved tolerance for endurance and stress exercises in the superficial quadriceps femoris muscles. In contrast, Crozara et al. (2015) evaluated the EMGFT of various small muscles, including biceps femoris, rectus femoris, vastus lateralis, and lateral gastrocnemius using two EMG methods.
Altın, C., & Er, O. (2016). Comparison of different time and frequency domain feature extraction methods on elbow gesture’s EMG. European Journal of Interdisciplinary Studies, 2(3), 35-44.
Crozara, L. F., Castro, A., De Almeida Neto, A. F., Laroche, D. P., Cardozo, A. C., & Gonçalves, M. (2015). Utility of electromyographic fatigue threshold during treadmill running. Muscle & Nerve, 52(6), 1030-1039.
Ertl, P., Kruse, A., & Tilp, M. (2016). Detecting fatigue thresholds from electromyographic signals: A systematic review on approaches and methodologies. Journal of Electromyography and Kinesiology, 30, 216-230.
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Lozano-García, M., Sarlabous, L., Moxham, J., Rafferty, G. F., Torres, A., Jané, R., & Jolley, C. J. (2018). Surface mechanomyography and electromyography provide non-invasive indices of inspiratory muscle force and activation in healthy subjects. Scientific Reports, 8(16921), 1-13.
Mahmutović, S., Sprout, E. Y., Fontaine, J. C., Buskirk, T. M., Galen, S. S., & Malek, M. H. (2016). Test-retest reliability of the electromyographic fatigue threshold for cycle ergometry. Muscle & Nerve, 53(5), 803-807.
Malek, M. H., & Coburn, J. W. (2012). The utility of electromyography and mechanomyography for assessing neuromuscular function: A noninvasive approach. Physical Medicine and Rehabilitation Clinics, 23(1), 23-32.
Morse, J. J., Pallaska, G., Pierce, P. R., Fields, T. M., Galen, S. S., & Malek, M. H. (2016). Acute low-dose caffeine supplementation increases electromyographic fatigue threshold in healthy men. Journal of Strength and Conditioning Research, 30(11), 3236-3241.