An article published in the Journal of Applied Physiology on April 29th shed light on some critical applications for the use of near-infrared spectroscopy (NIRS) in endurance sport – The Balance of Muscle Oxygen Supply and Demand Reveals Critical Metabolic Rate and Predicts Time to Exhaustion
Multimodal Fitness or High Intensity Functional Training (HIFT) has gained a considerable following in the past few years. It provides a class based setting that aims to improve metabolic conditioning, strength, and gymnastic ability, amongst other things. Over the first quarter of the year, I have been attending classes. Admittedly, I was a bit skeptical at first but have grown to love the challenge of the different movements and ability to scale any movement in order to complete the workout. One of the major challenges that people going to these classes, myself included, face is the ability to properly pace yourself throughout the entire workout. While some very experienced athletes know that they can complete X number of body weight squats with Y amount of rest, this pacing gets way more challenging when you couple squats with burpees, or other movements.
5-1-5 assessments can be used to estimate the system that is most limiting to an athlete’s performance. These systems include 1) pulmonary, the lung’s ability to uptake, and transfer oxygen to the blood 2) cardiac, the heart’s ability to deliver oxygen rich blood to the muscle and get rid of metabolites and 3) skeletal muscle, the mitochondria’s ability to utilize oxygen in the working muscle Whole-body exercise requires multifaceted integration of biological systems in order to sustain locomotion, if one of these systems is inadequate then fatigue is imminent. In this post, I want to take a deeper dive into what could be responsible for a pulmonary limitation and what could be leading to fatigue in athletes with this limitation, a few papers are cited but the main one spurring this post is by Dempsey et al. 2006.
VO2max, thresholds, and efficiency are thought to be and certainly do have considerable predictive power for endurance performance. They are great global variables to measure and monitor how an athlete is coping with the stress of long endurance athletics. However, most metabolic devices are bulky, require uncomfortable mouth pieces, backpacks, or other restrictive equipment which can interfere with an athlete’s performance. They also fail to directly measure the stress of arguably the most important organ during exercise, the skeletal muscle. Recently, the ability for skeletal muscle to utilize oxygen measured by near-infrared spectroscopy (NIRS) has been shown to the best predictor of endurance performance in trained cyclists. Therefore in order to gain the best picture of an athlete’s physiology, these global measures should be accompanied by devices that can measure local stress.
My journey into physiological testing and program design started approximately 20 years ago when working with ironman triathletes, skiers, cyclists and mountain bikers. All around me were coaches prescribing general triathlon programming without knowing their athlete’s specific performance limitations. How can I prescribe an athlete specific program to improve performance without identifying their limitation(s)?
Topics: Zones and Other Metrics
Introduction. Over the last few weeks a case study of 5 weeks of high intensity interval training has been completed. To refresh your memory, the athlete, a well-trained cyclist, completed five consecutive weeks of 5-10 reps of 30-40s at ~600w (30-60s rest). The athlete was able to complete at least 5 intervals per training session, however during workout 4 only 5 intervals were completed and there was a large discrepancy in how well the athlete could desaturate leading to a truncated workout, and ultimately and much better workout the following week. In this post I want to touch on some things to be aware of as a coach using Moxy, as well as some practical applications using the data. These applications will include recommendations for warm-ups, knowing when to stop an athlete’s workout.
Introduction. In the last blog post I outlined how Moxy was used over the course of five weeks to inform an athletes training. More specifically, the athlete, a well-trained cyclist, completed five consecutive weeks of 5-10 reps of 30-40s at ~600w (30-60s rest). The athlete tracked power output, heart rate, and SmO2. They allowed SmO2 to recover to at least 60% before starting the next interval. While its been suggested that Moxy could be a good tool to help autoregulate workouts there haven’t been too many case studies relating to how Moxy values change over time. In this post, I want to walk-through how SmO2 and power trends changed over the course of five weeks of concerted training. Before diving into the details I want to acknowledge that five weeks may not be adequate time to truly monitor chronic adaptations to exercise in trained athletes, more than likely, what these training sessions will help us understand is how things, like acute training load and stress can affect the outcome of a work.
The goal of training is to improve performance. This typically involves skirting a very thin line between maximizing performance and overtraining. However, training isn’t the only stress that our bodies undergo throughout the day. Stress can present itself through things like work, home, relationships, and pretty much every other aspect of life. And a huge challenge when training for high performance is balancing stress and workload with proper recovery. There have been many attempts to monitor all stress levels, to get an idea of how hard to push the body during a training session, and while things like heart rate, and power output, seem to do a decent job at monitoring training stress, there is still a general lack of guidelines of when to terminate a workout early based on these factors. Monitoring skeletal muscle oxygenation (SmO2) offers a more objective means of monitoring how the muscle is responding to the stress of training. Arguably, one of the largest benefits of monitoring SmO2 during workouts is the ability to autoregulate workouts. While this is an extremely powerful tool to monitor the acute effects of exercise and tailor workouts to an individuals’ physiology. It’s been shown that heart rate at the same power output improves over time, the highest maintainable power output during an endurance event increases and VO2max increases with proper training, yet, very little has been done to monitor how training effects SmO2. In the next few posts I want to walk through a case study to detail changes to an athletes’ physiology over the course of 5 weeks of training. This first post will detail the set-up and give proper background information, the second post will look at the acute effects of each workout, and the final post will detail the patterns of change throughout the 5 weeks.
Near-infrared spectroscopy (NIRS) devices have seen growing popularity in research and sporting application over the last decade because of their ability to non-invasively determine muscle oxygen saturation changes during real-time activities. These devices have the potential to change the way exercise is prescribed. However, most NIRS devices are too expensive for consumer use and/or require large power sources and cords, relegating athletes and coaches to only using these devices in a laboratory setting. NIRS devices use a few different methods to determine changes in muscle oxygenation, which I won’t go into detail in this post, but the least cost prohibitive is a method called continuous-wave NIRS. This involves emitting 2 to 4 different wavelengths of light into the tissue of interest and measuring changes in the intensity of light to determine how tissue oxygenation is changing. One major drawback of using most CW-NIRS devices is that they use 2 wavelengths of light while assuming that the tissue the light is passing through remains constant which limits these devices to ONLY reporting changes in muscle oxygenation. Indeed, these devices can estimate percent changes in oxygenation, but only after a calibration step is completed and applied to the data after tests are finished.
Introduction. In the last post how to complete a repeat desaturation protocol was discussed. This protocol is especially useful for multimodal and team sport athletes. Briefly, using a sport specific exercise modality, have an athlete complete repeated sprint intervals (~20s) until they can no longer desaturate or recover SmO2 to the same extent as the start of the workout. Using this data, coaches and athletes can get an idea of sprint endurance capacity which will inform substitution patterns in team sports activities and pacing strategies for other sports. In this blog post I want to walk through an example of a repeated desaturation protocol completed by a cyclist to get an idea of his capacity for accelerations/attacks during a race.