Can neuromuscular fatigue be measured with thermography in athletes?

Thermography appears to have an interesting role in the assessment of neuromuscular fatigue, both during and after exercise. In a study from the University of Ljubljana in Slovenia, they demonstrate the usefulness of thermographic monitoring for the relationship between skin temperature to neuromuscular fatigue.

What is muscle fatigue?

The term muscle fatigue is used to denote a transient decrease in the ability to perform physical actions (Enoka et al. 2008), as well as in a person’s ability to exert force (Lorist et al. 2002). These definitions apply only to sports and high-performance environments, as can be seen in figure 1 (Baudry et al. 2007). On the other hand, muscle fatigue found in clinical environments is more related to pathology or its consequences, such as loss of function, chronic pain, or bed rest (Bailey et al. 2007).

Figure 1. Average torque exerted by young and older adults for five sets of 30 repetitions. See the loss of performance when fatigue sets in and the increase in performance after interset rest. Adapted from Baudry et al. (2007).

Roughly speaking, in a moment of muscle fatigue, one or more of the physiological processes that allow contractile proteins to generate force are impaired. More specifically, the mechanical impairment produced by fatigue is directly dependent on the task being performed. This effect, known as task dependence, is one of the most studied principles in the field over the last 70 years (Scherrer, 1953; Asmussen, 1979; Enoka & Stuart, 1992). By definition, there is no single cause of muscle fatigue and the dominant mechanism is specific to those processes that are stressed during strenuous exercise (Cairns et al. 2005). Therefore, in this article, we will discuss “local” neuromuscular fatigue and in future articles, we will deal with “global” fatigue more dependent on the cardiovascular system.

Neuromuscular (local) fatigue and loss of performance

We can consider a muscle to be fatigued when it fails to maintain performance after a task, which may be endurance or strength. However, the reason for both can be very different:

1- in the first, we tend to think that fuel supply via oxidative pathways has been exhausted;

2- in the last, we are inclined to look for an explanation more related to the central nervous system.

But in either case, the consequence is a loss of peak performance.

This depends on many factors, such as intensity, type of exercise, type of muscle contraction, whether compression is used or not, and so on.

There are some tests that allow us to measure or estimate muscle fatigue.

Electromyography (EMG) provides an objective view of the loss of performance associated with neuromuscular fatigue. Fatigue is known to be reflected in the EMG signal as an increase in amplitude and a decrease in frequencies (Kallenberg et al. 2007). In figure 2, we can observe the decrease in the contraction performance of a muscle during a period of neuromuscular fatigue (Fernandez et al. 2007).

Figure 2. Averaged M-wave periodograms at the beginning (dotted line) and during the fatigue period of the stimulation protocol in the study by Fernandez et al. (2007).

Are there other technologies that help to understand this complex process? 

Thermography and neuromuscular fatigue studies

The results of the study by Bartuzi et al. (2012) suggest that infrared thermography can be a complementary method to assess neuromuscular fatigue in low-intensity muscle contractions, being a fast, non-invasive technology with acceptable levels of accuracy. Similarly, in the study by Priego-Quesada et al (2015), a significant inverse relationship was observed between changes in skin temperature and changes in overall neuromuscular activation of the vastus lateralis (r<-0.5 and p<0.04). A significant positive relationship was observed between skin temperature and low-frequency components of vastus lateralis neuromuscular activation (r>0.7 and p<0.01).

It appears that thermography can differentiate skin temperature changes also associated with intense single-leg exercise, perhaps shedding some light on the relationship between thermography’s ability to assess when the central nervous system is not highly stressed (Stewart et al. 2020). That seems to be the conclusion following the recent study by Shakhi et al. (2021), which shows us evidence that skin surface temperature can be used to monitor and predict neuromuscular fatigue in low-intensity dynamic exercise.

Different post-exercise thermal patterns can be identified depending on the type of stimulus and the muscle fatigue produced. In a review by (Hillen, B et 2020) the authors point out that depending on the type of exercise performed the skin response will be different. 

Whereas, in predominantly aerobic exercises there will be a tissue perfusion response, where the most common is to see a “Dalmatian” or “hot spot” pattern during the test and post-exercise, these types of demands will lower the body temperature, with the aim of thermoregulating the body during the activity. (See figure x for temperature during an incremental test). 

Figure 3. Incremental cycling test and measurement of the skin temperature of the thigh, grey line, and forearm, black line.

Exercises that demand resistance to force at a low or moderate intensity as seen in previous sections will increase the temperature of the exercised region with two types of patterns, the first more related to the large muscle groups where the response will have a venous pattern when fatiguing large muscle groups locally, these muscle groups with a greater blood supply will demand an increase in the light of the circulatory system causing vasodilation, and therefore an increase in the temperature of the region if we reach its exhaustion. 

Finally, when we locally fatigue small muscle groups, the thermodynamic muscle activation itself will increase the temperature of the region, in this case, the response will be a homogeneous increase in temperature due to the energetic solicitation of the region.

These thermal patterns can be seen in figure 4 extracted from the article by (Hillen, B et 2020).

Figure 4. Thermal patterns of the skin in response to a different type of exercise. Perfusion: due to predominantly aerobic exercise. Venous: due to strength endurance exercise on large muscle groups. Homogeneous: due to strength exercise in small muscle groups.

However, when the stimulus produces delayed onset muscle soreness (DOMS), thermography does not provide much extra information (Stewart et al. 2020) and has even been shown to be ineffective in predicting DOMS 24h after exercise (Priego-Quesada et al. 2020).

An interesting case study on the relationship between skin temperature and neuromuscular fatigue is published by Hadzic et al. (2019), from the University of Ljubljana, Slovenia. They analysed the relationship between the power produced and the change in quadriceps skin temperature during a knee extension exercise (figure 3). After correlational analysis, they showed that there is a significant negative correlation between increased skin temperature and decreased power (r = -0.543, p = 0.036). Based on these findings, in a linear regression model, the power that the quadriceps would be able to produce could be predicted from skin temperature. When analysing the control limb, no such relationships were found.

Figure 5. Region of interest in the quadriceps skin in a subject performing knee extension exercise to fatigue. (Hadzic et al. 2019)

Similar results were found in Escamilla et al. (2017), where, in addition to corroborating the thermal increase related to neuromuscular fatigue, they did show an approximately 50% lower increase in the control limb. In addition, by having a larger sample (n=17), they were able to divide into two groups (high-trained, n=8 and low-trained, n=9), thus demonstrating a lower thermal increase in trained individuals, despite maintaining the same intensity (70% 1RM).

Figure 6. A sequence of images from the study by Escamilla et al. (2017) First image before training, the second image just after finishing the training protocol, the third image 30 minutes after training, and the last image 60 minutes after training.

Conclusion

Although much research remains to be done, there seems to be a clear correlation between the level of neuromuscular fatigue and the increase in skin temperature of the locally exercised muscle region. To date, there is insufficient evidence to explain the mechanisms that produce an increase in the temperature of the region in the presence of marked neuromuscular fatigue, at low, medium, and high intensities. However, recent studies seem to demonstrate the usefulness of thermography in the estimation of neuromuscular fatigue, which opens up a very interesting field of study in the non-invasive monitoring of training loads.

Future articles will deal with “global” fatigue, where the opposite mechanisms by which body temperature drops after this type of training will be presented. Thermography and fatigue.

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