Measuring Muscle Oxidation in Athletes with Near-Infrared Spectroscopy

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Spectroscopy SupplementsAdvances in Infrared Spectroscopy for Today’s Spectroscopists
Volume 39
Issue s8
Pages: 20–21

The Moxy Monitor is a portable near-infrared (NIR) spectroscopy device that can be used to measure muscle oxygen saturation in real-world settings and everyday training. A recent article authored by scientists from the Institute of Sport and Preventive Medicine, part of the University of Saarland (Saarbrücken, Germany), discusses their investigation of the absolute and relative test-retest reliability of the Moxy Monitor, as well as their investigations into side differences of oxygen saturation at the vastus lateralis muscle of both legs in male cyclists. The Moxy Monitor is a small, wearable sensor that utilizes infrared light to continuously monitor oxygen saturation (SmO2) levels in the muscles of athletes. Spectroscopy spoke to Philip Skotzke from the Institute of Sport and Preventive Medicine, corresponding author of the article, about his team’s research and their findings.

In your paper (1), you state that near-infrared (NIR) spectroscopy measuring muscle oxygenation can be considered an advanced technology to improve objective training monitoring. How can NIR spectroscopy be used to do this?

NIR spectroscopy-measured muscle oxygenation is a relatively new technology in sport science, and only in recent years have new and affordable wearable devices been available for athletes and coaches. What makes NIR spectroscopy interesting is that it allows us to measure the local metabolism of a single muscle during exercise in real time. This can be a huge advantage over existing technologies that only measure whole-body physiological responses, like heart rate, lactate, or pulmonary oxygen uptake. Knowing what is happening in the muscles used during exercise not only allows a better understanding of how hard you are going, but also helps you adjust your efforts to meet the goal of your training session.

Can you explain how the NIR monitor functions, in terms of wavelengths measured and data processing used?

The NIR monitor used in this study measures muscle oxygen saturation (SmO2) and total hemoglobin and myoglobin using continuous-wave NIR spectroscopy technology. One light emitter sends light of four wavelengths between 630 and 850 nm into the underlying tissue, and two detectors spaced 12.5 and 25 mm apart measure the reflected light. A proprietary algorithm based on Monte-Carlo simulation is used to: 1) isolate muscle from superficial adipose tissue; 2) overcome the issue of continuous-wave NIR spectroscopy of unknown differential path length factor; and 3) provide an a priori 0% to 100% scale. The sampling rate can be set to 0.5–2 Hz. For this study, the sampling rate was set to 0.5 Hz, with a rolling average smoothing over the last five samplings. The device wirelessly sends the output via ANT+ and Bluetooth to your recording device.

Is it possible to use spectroscopic methods other than NIR spectroscopy to improve training monitoring?

To our best knowledge, NIR spectroscopy is currently the only method that is available for sports applications outside of laboratory settings.

Your research investigated the reproducibility of SmO2 measured by a portable near-infrared spectroscopy device at different power outputs between three—instead of the previously investigated two—cycling incremental step tests performed under similar conditions. What benefit did analyzing the additional step test provide?

This decision was made for statistical reasons. Adding a third trial allows us to achieve higher statistical power with the same sample size. In other words, the more trials performed, the closer we can understand the true day-to-day variation, meaning that our results are less influenced by tests that are outliers. For example, if only two trials were performed and a participant comes to one of them in a more fatigued state, and therefore has lower muscle oxygenation, we might overestimate the day-to-day variability.

How does knowing SmO2 optimize athletic performance?

Muscle oxygen saturation (SmO2) is the balance between oxygen delivery to and oxygen utilization by the muscle. Having oxygen available in the locomotor (working) muscles is crucial to sustain prolonged exercise. Generally, high SmO2 shows that oxygen delivery is sufficient and that the work does not require much oxygen. This indicates that the current workload is relatively easy for that person, and is sustainable for a long time. In contrast, if SmO2 is low or decreases over time, the oxygen delivery cannot keep up with the demand, ultimately making the exercise unsustainable. Finding the highest speed where delivery and utilization are in balance allows optimized athletic performance.

What sort of specific pre-exercise and exercise protocols did your test subjects go through?

We tested cyclists and triathletes who actively participate in competitions. The day before the tests, participants refrained from fatiguing (long or intensive) exercise, and kept their nutrition similar between all tests.

During the laboratory visits, body weight, body fat percentage, and skinfold thickness at the vastus lateralis muscle were measured, and the NIR spectroscopy devices were placed on the vastus lateralis of both legs before the incremental cycling test started. The test started at 1.0 watt/kg body weight, and the workload was increased every 5 min by 0.5 watt/kg. The participants cycled until exhaustion.

What were your findings?

Our main finding was that the test-retest reliability of SmO2 is around 6% SmO2 at the same power output measured by the standard error of measurement. That is, variations in SmO2 of lower up to 6% between tests can be attributed to normal day-to-day variability.

Our second finding is that there is no systematic difference between SmO2 of the dominant and non-dominant leg, but muscle oxygenation between sides can differ by 20% (95% Limits of Agreement).

Do your findings correlate with what you had hypothesized?

Previously published research came to different conclusions regarding the test-retest reliability during higher workloads. Therefore, we hypothesized that when choosing the appropriate statistical method, test-retest reliability is similar between low and high workloads. Our results are in line with this hypothesis, as test-retest reliability was around 6% SmO2 for all workloads.

We hypothesized to observe side differences, as it has been shown previously that power output is different between the dominant and non-dominant leg in cycling. However, we could not find a systematic difference between legs. The side differences appeared to be random, and not related to leg dominance.

Was there anything particularly unexpected that stands out from your perspective?

Most research using NIR spectroscopy in sport science only measure one limb. In the light of our findings, this seems to be problematic, as the athletic performance usually is produced by both limbs. Our findings indicate that unsystematic side differences exist, and that measuring both sides might provide a better understanding of athletic performance.

Were there any limitations or challenges you encountered in your work?

Unfortunately, our study is limited to male endurance athletes that are relatively lean. As the thickness of the adipose tissue layer has an impact on measured SmO2, and females tend to have higher adipose tissue thickness, the findings cannot be generalized to a bigger population. A problem we encountered was that we had a lot of missing data at higher intensities that could be due to the wireless connection of the NIR spectroscopy devices to the recording device. As not all tests could be repeated, this reduces the number of participants that could be included for the statistical calculations for high power outputs.

What best practices can you recommend in this type of analysis for both instrument parameters and data analysis?

We recommend the following considerations:

  • Choose a muscle specific to the exercise modality you want to investigate.
  • Ideally, measure SmO2 on both sides.
  • If this is not possible, choose one side and one muscle, and always place the same NIR spectroscopy device at the exact same location. We recommend identifying and using the dominant leg.
  • Be aware that there might be missing data. Having a second device on the other limb can be used as back-up.
  • For the analysis, exclude at least the first 60 s after a change in workload, as SmO2 needs some time to stabilize.

Can you please summarize the feedback that you have received from others regarding this work?

Thus far, the feedback from the scientific community was very positive. Knowing how reliable a measurement device is will be crucial, not only for research, but also for athletes and practitioners. The unsystematic side differences were noticed as an especially important new finding.

What are the next steps in this research, and are you planning to be involved in improving this technology?

As sports scientists, we are interested in how new technologies can be implemented in the daily practice of athletes. Currently, our understanding on how SmO2 changes following different types of endurance training is limited. This is where our next research project using NIR spectroscopy will try to provide new insights.

Our work focuses on technological application. We do not plan to be involved in the development of the technology itself.

References

(1) Skotzke, P.; Schwindling, S.; Meyer, T. Side Differences and Reproducibility of the Moxy Muscle Oximeter During Cycling in Trained Men. Eur. J. Appl. Physiol. 2024. DOI: 10.1007/s00421-024-05514-2

Philip Skotzke is an aspiring young sport scientist interested in the physiology of endurance performance. His work focuses on the integration of new technologies to quantify training and bridge the gap between laboratory assessments and monitoring in real world conditions. Direct correspondence to: s8phskot@stud.uni-saarland.de●

Philip Skotzke is an aspiring young sport scientist interested in the physiology of endurance performance. His work focuses on the integration of new technologies to quantify training and bridge the gap between laboratory assessments and monitoring in real world conditions. Direct correspondence to: s8phskot@stud.uni-saarland.de

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