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Method Article
The purpose of this investigation was to assess whether using an infra-red thermal camera is a valid tool for detecting and quantifying the muscle soreness after exercising.
Delayed onset muscle soreness (DOMS), also known as exercise induced muscle damage (EIMD), is commonly experienced in individuals who have been physically inactive for prolonged periods of time, and begin with an unexpected bout of exercise1-4, but can also occur in athletes who exercise beyond their normal limits of training5. The symptoms associated with this painful phenomenon can range from slight muscle tenderness, to severe debilitating pain1,3,5. The intensity of these symptoms and the related discomfort increases within the first 24 hours following the termination of the exercise, and peaks between 24 to 72 hours post exercise1,3. For this reason, DOMS is one of the most common recurrent forms of sports injury that can affect an individual’s performance, and become intimidating for many1,4.
For the last 3 decades, the DOMS phenomenon has gained a considerable amount of interest amongst researchers and specialists in exercise physiology, sports, and rehabilitation fields6. There has been a variety of published studies investigating this painful occurrence in regards to its underlying mechanisms, treatment interventions, and preventive strategies1-5,7-12. However, it is evident from the literature that DOMS is not an easy pathology to quantify, as there is a wide amount of variability between the measurement tools and methods used to quantify this condition6. It is obvious that no agreement has been made on one best evaluation measure for DOMS, which makes it difficult to verify whether a specific intervention really helps in decreasing the symptoms associated with this type of soreness or not. Thus, DOMS can be seen as somewhat ambiguous, because many studies depend on measuring soreness using a visual analog scale (VAS)10,13-15, which is a subjective rather than an objective measure. Even though needle biopsies of the muscle, and blood levels of myofibre proteins might be considered a gold standard to some6, large variations in some of these blood proteins have been documented 6,16, in addition to the high risks sometimes associated with invasive techniques.
Therefore, in the current investigation, we tested a thermal infra-red (IR) imaging technique of the skin above the exercised muscle to detect the associated muscle soreness. Infra-red thermography has been used, and found to be successful in detecting different types of diseases and infections since the 1950’s17. But surprisingly, near to nothing has been done on DOMS and changes in skin temperature. The main purpose of this investigation was to examine changes in DOMS using this safe and non-invasive technique.
1. The Exercise
2. Infra-Red Camera Preparation & Setup
* A series of tests were done at our labs using the FLIR 660 IR Camera (Fig. 8), where we compared images of the skin at different angles (0 (perpendicular), 15, 30, 45, and 60 degrees), and at different distances (1, 2, and 5 meters) from the skin, to accurately detect the temperature of the skin. All images were compared to calibrated thermocouples, and the best correlation between the images and the thermocouple readings was at a perpendicular angle and at a distance of 1 meter away from the skin (r = 0.93). The different angles and distances caused a pixilation loss, and decreased the overall correlation between the images and the thermocouple readings.
3. Image Acquirement
4. Image Processing & Analyses
5. Visual Analog Scale & Blood Analysis
6. Representative Results
The results of IR thermal images taken during this investigation are clearly represented in figure 1. Images taken at the 3 time periods (pre-exercise, 24 hours post-exercise, and 48 hours post-exercise) for the exercised arms of the 41 subjects, showed a noticeable increase in temperature on day 2 (24 hours post-exercise) when compared to pre-exercise temperatures, and temperatures taken at 48 hours. As shown in figure 1, the average skin temperature was 32.80 +/- 1.03 °C for day 1 (pre-exercise), and 33.96 +/- 1.46 °C for day 2 (24 hours post-exercise), and 32.82 +/- 1.29 for day 3 (48 hours post-exercise). This difference in skin temperature from day 1 to day 2 was significant (ANOVA p < 0.01).
However, for the un-exercised arm, changes amongst the 3 time periods were not evident. Figure 1 shows that the average skin temperature was 33.08 +/- 0.83 °C for day 1 (pre-exercise), and 32.79 +/- 1.42 °C for day 2 (24 hours post-exercise), and 33.17 +/- 0.95 for day 3 (48 hours post-exercise). This difference in skin temperature over the 3 days was not significant (ANOVA p = 0.38).
The results of the pain readings from the VAS are shown in figure 2. As seen in figure 2, the reported pain had a dramatic increase on days 2 and 3. Pain levels of the exercised muscle increased from 3.6 +/- 6.1 on day 1, to 36.3 +/- 22.8 on day 2, and 37.5 +/- 25.3 on day 3. This increase from day 1 was significant (ANOVA p < 0.01).
The results of the myoglobin concentration levels are shown in figure 3. As seen in this figure, there was hardly any change between the 2 myoglobin concentrations on day 1 (pre, & 30 minutes post exercise). But on day 3, the increase in myoglobin was very large. This increase on day 3 was approximately 147 nanograms per milliliter (ng/mL) of blood when compared to the first 2 concentrations on day 1. Myoglobin concentrations were 30.12 +/- 7.66 ng/mL at baseline, 31.66 +/- 11.89 ng/mL 30 minutes post exercise, and 178.96 +/- 249.51 ng/mL on day 3. This increase on day 3 was highly significant (ANOVA p < 0.01).
A correlation analysis was done between the skin temperatures obtained from the IR images, and the VAS soreness levels. It was found that there was a considerable correlation between the VAS readings on day 2, and the skin temperature measurement on day 2. This correlation was significant (r = 0.312, p < 0.05). However, there was no evident correlation between the VAS readings and the skin temperatures on day 3. This correlation was insignificant (r = 0.047, p = 0.77).
Figure 1. A representative graph of the differences in skin temperature in the exercised arms (Diamonds), and un-exercised arms (Squares) of the 41 subjects over the 3 day time period.
Figure 2. A representative graph of the differences in perceived muscle soreness measured with the VAS over the 3 day time period for all the 41 subjects.
Figure 3. A representative graph of the differences in myoglobin concentrations for all the 41 subjects over the 3 time periods.
Figure 4. A) a typical IR image of a subject's exercised arm before the exercise. B) an IR image of the same subjects arm 24 hours after the exercise.
Figure 5. A) a typical IR image of a subject's un-exercised arm before the exercise. B) an IR image of the same subjects arm 24 hours after the exercise.
Figure 6. An illustration of the 4 regions of interest for analyzing the thermal image of the arm.
Figure 7. Software interface for the "ThermoVision ExaminIR" showing the 4 boxes of interest on an IR image of an exercised arm. Also shown are the statistical interpretations for each box.
Figure 8. The IR thermal camera used for this investigation (FLIR 660).
Figure 9. A) The Setup of the IR Camera 1 meter away from the subjects arm. B) The LED lights used in the lab where the images were taken.
Figure 10. A) The BioPac Modules used for measuring the muscle strength. B) The strain gauge device fixed to a 45° angled bench and hooked to the BioPac system.
Figure 11. A typical subject exerting force on the strain gauge device.
Figure 12. A subject undergoing the exercise protocol for inducing the muscle soreness.
The primary purpose of this investigation was to assess the usefulness of thermal IR imaging in detecting and measuring muscle soreness after strenuous exercise, and our results suggest that IR imaging could be a valid technique for detecting DOMS, especially within the first 24 hours of exercising. This is not surprising, as Pennes18 provided a very detailed model of heat flow from muscle to skin in limbs. This model predicts that heat in deeper tissues such as muscles can be dissipated into blood and into th...
No conflicts of interests declared.
We wish to acknowledge a contract (WS1763368) from Pfizer Pharmaceuticals for support in this work. We would also like to thank the Saudi Arabian Ministry of Higher Education (MOHE) for their support.
Name | Company | Catalog Number | Comments |
Infra-Red Thermal Camera | FLIR Systems Inc. | FLIR SC660 | |
Thermal Infra-Red Analysis Software | Thermo Fisher Scientific, Inc. | Software Version 1.10.2 | |
Bi–lectric Amplifier Module | Biopac Systems, Inc. | DA100C | The DA100C provides variable gain settings, and adjustable voltage references. |
Analog to Digital Converter Module | Biopac Systems, Inc. | MP100 | |
Automated enzyme Immunoassay Analyzer | Tosoh Corp. | AIA -360 | This device was used to analyze the blood samples, and obtain the myoglobin readings. |
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