The Concept of Surface and Fine Wire EMG

Subject: Health IT
Pages: 5
Words: 1187
Reading time:
4 min
Study level: Master

Differences Between Surface EMG and Fine Wire (or Needle) EMG

Electromyography (EMG) is a technique used to measure the action of muscles, thereby producing data that enable the comprehension of muscle coordination during movement. Two modes of EMG exist, namely invasive and noninvasive. Surface EMG is an adaptable and non-invasive approach to evaluating the activation of the motor unit for small or large muscle groups during diverse exercise modalities (Mahmutovi? et al., 2016). In this technique, electrodes are put on the surface of the skin on the muscles to be tested. Conversely, fine wire or needle EMG is an invasive technique that is used for the same purpose. However, the needles or wires are inserted into the muscles of interest (Malek & Coburn, 2012).

Studies involving the comparisons between the recording of surface EMG and fine wire EMG show differences at various exercise intensities and muscle groups. For instance, when muscles are contracting at low intensities, surface EMG electrodes are capable of recording extra myoelectric readings. However, in high load isometric tasks, there are no significant differences in the readings between the two methods. The additional readings are attributed to crosstalk from adjacent muscles (Semciw, Neate, & Pizzari, 2014).

Another major difference between surface EMG and fine wire EMG is that the former has a larger pick-up area than the latter method. Surface EMG can pick up the activity of exterior muscles whose depth does not exceed 1.8 cm. Nonetheless, there is a difference in signals obtained from deep muscles of the same type using the two techniques. Surface EMG can detect twice the level of muscle crosstalk than fine wire EMG (Rajaratnam, Goh, & Kumar, 2014). This observation suggests that surface EMG is more sensitive than fine wire EMG.

The Concept of the EMG Fatigue Threshold

EMG fatigue threshold has been defined as the physical working potential at the onset of exhaustion (Mahmutovi? et al., 2016). Identifying fatiguing and non-fatiguing exercises is important for various purposes. In athletics, it is important to help athletes run at the best speed in a marathon. Conversely, physiotherapists need to identify non-fatiguing exercises or intensities to help their clients perform and sustain activities of daily living (Khan, Lawal, Kapture, Swingle, & Malek, 2017).

These exercises can be identified by measuring the neuromuscular fatigue threshold using EMG signals obtained from different muscle groups. The EMG amplitude domain that shows an increase in muscle recruitment, muscle firing, or both parameters is important. Studies show that a rise in EMG amplitude versus power output occurs whenever an individual engages in increasing, nonstop exercise (Khan et al., 2017). Therefore, EMG can be used to pinpoint exercises with high intensity that can be sustained for protracted periods without resulting in substantial increases in EMG amplitude versus time correlation.

However, for the EMG fatigue threshold to be used as a reliable indicator in estimating fatigue, there is a need to validate it. Consequently, several researchers have conducted studies to determine its validity under various circumstances. For example, Mahmutovi? et al. (2016) tested the intersession dependability of the EMG fatigue threshold for cycle ergometry. It was known that the amplitude of EMG, which quantified the recruitment of motor units, the firing rate, or both parameters, was a dependable yardstick during cycle ergometry. In contrast, the validity of EMG frequency, which was assumed to indicate the conduction speed of the action potentials of the muscle, was low. Mahmutovi? et al. (2016) enrolled 10 men and subjected them to deliberate fatigue on a cycle ergometer.

Linear regression was used to evaluate the EMG amplitude versus time associations for the power productivity of the quadriceps femoris muscles. During the analysis, the mean of the highest power output generated an insignificant slope coefficient, as well as the lowest output that spawned a significant gradient coefficient. Data from two trials were used to compute the intraclass correlation coefficient, which was 0.85 at a 95% confidence interval. These findings were considered excellent, which led to the authors concluding that the EMG fatigue threshold for cycle ergometry was an unfailing measure for evaluating muscle lethargy.

Several studies have been done to improve the fatigue threshold, including the use of food supplements to enhance the physical performance and general wellbeing of athletes. Such food supplements are referred to as ergogenic aids, which can be described as substances that boost the production of energy, thereby conferring sportsmen with a competitive advantage (Jerônimo et al., 2017). For example, it is reported that the consumption of caffeine raises tolerance in different types of exercise, including endurance and strength (De Poli, Miyagi, Nakamura, & Zagatto, 2016).

Caffeine is assumed to improve the anaerobic potential by modulating the oxygen equivalents attributed to the glycolytic and phosphagen metabolic pathways. Consequently, the idea of caffeine as an ergogenic aid to diminish physiological and cognitive fatigue is promising. Morse et al. (2016) confirmed that low-dose caffeine supplementation (200 mg) administered an hour before exercise suspended neuromuscular exhaustion in the quadriceps femoris muscles.

Another important ergogenic aid that affects the EMG threshold is creatine. This supplement works by promoting the production of energy in the form of adenosine triphosphate (ATP) in the muscles. Jerônimo et al. (2017) also found that caffeine (6 mg per kg) acted synergistically with creatine (3 g) as ergogenic aids and led to enhanced muscle EMG activity when administered concurrently to athletes for a week.


De Poli, R. D. A. B., Miyagi, W. E., Nakamura, F. Y., & Zagatto, A. M. (2016). Caffeine improved time to exhaustion but did not change alternative maximal accumulated oxygen deficit estimated during a single supramaximal running bout. International Journal of Sports Nutrition and Exercise Metabolism, 26(6), 549-557.

Jerônimo, D. P., Diego Germano, M., Baccin Fiorante, F., Boreli, L., da Silva Neto, L. V., de Souza, R. A.,… de Morais, A. C. (2017). Caffeine potentiates the ergogenic effects of creatine. Journal of Exercise Physiology Online, 20(6), 66-77.

Khan, F. L., Lawal, J. M., Kapture, D. O., Swingle, J. D., & Malek, M. H. (2017). Revisiting the single-visit protocol for determining the electromyographic fatigue threshold. The Journal of Strength & Conditioning Research, 31(12), 3503-3507.

Mahmutovi?, 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.

Rajaratnam, B. S., Goh, J. C. H., & Kumar, V. P. (2014). A comparison of EMG signals from surface and fine-wire electrodes during shoulder abduction. International Journal of Physical Medicine & Rehabilitation, 2(4), 1-6.

Semciw, A. I., Neate, R., & Pizzari, T. (2014). A comparison of surface and fine wire EMG recordings of gluteus medius during selected maximum isometric voluntary contractions of the hip. Journal of Electromyography and Kinesiology, 24(6), 835-840.