Thanks to my current job, I have been lucky enough to mess around with a bunch of cool, sports science training tools. One of the recent devices I have been playing with is called a Moxy Monitor. In short, it allows me to see the local metabolic demands of the muscle via anaylsis of muscle oxygen saturation levels “SmO2%” (amount of oxygen my muscles are using) and the changes in local blood flow.
Without diving too far into the science, the SmO2% can tell you how much oxygen is being released from the blood stream (capillary level) to the local tissue. The rate at which SmO2% is reduced (desaturated) and the rate at which it returns (resaturates) to baseline during exercise can provide some interesting insights.
As some may know, I am a velocity nerd. I think it is one of the most unique measuring tools available. So naturally, I wanted to use the Moxy Monitor in conjunction with a Tendo Unit to get an understand of how fatigue was manifesting itself during a velocity drop off squat session.
Image 1The squat session was pretty straightforward. I established a maximal load at roughly 0.55m/s and performed reps until my velocity dropped below 0.50m/s (0.05 m.s drop off). This 11% velocity drop off was in theory, going to limit the amount of lactate and acidity present in the muscle (typically this starts to accumulate with a 30% drop off).
Below is a picture of my SmO2% during my working sets (9 in all). Working sets are marked with a yellow dot at the peak of the desaturation level for each set. Each set is marked by an immediate decrease and then a rise back to base line (V – shape).
There are a couple of interesting takeaways from the above graph:
1: During all working sets, SmO2% returned back to working baseline
2: During all working sets, SmO2% peak desaturation trended downward (larger levels of desaturation)
3: All SmO2% curves appeared to be “V-shaped” with a consistent slope returning to baseline
According to my initial thoughts, I felt that the small velocity drop off ~11% would result in minimal acidity and lactate accumulation in the muscle and thus, would require little oxygen for restoration during recovery (assuming I had complete recovery between sets, which it appears I did).
Looking back at the graph, we can see that the desaturation curve all remained in a “V-shape”, indicating a rapid utilization of oxygen during the load, but also a rapid restoration of oxygen once the load was removed (I racked the bar after a set).
If large amounts of acidity and metabolic accumulation were present in the local tissue, one would expect to see a very slow, return to Smo2% (bottom right graph of figure 2). This would be due to the fact that the working muscle may not be actively contracting, but instead the low pH environment and high levels of C02 would increase the amount of oxygen disassociation (Bohr Effect) from the hemoglobin. However, with the utilization of such small velocity drop offs, this type of restoration pattern was never seen.
Thus, one might be able to draw the conclusion that fatigue was not induced by peripheral metabolic demands, but instead due to more central mechanisms. This is indicated in the failure to maintain velocity during all my working sets and the eventual failure of velocity maintenance by my 9th set, despite the fact that there were little to no signs of acidity present in the muscle.
Another side of the coin could be that an increase in desaturation levels might have been an indicator of how quickly energy systems were beginning to “fail”. While performing my working sets, I assumed that desaturation would eventually max out and on my final set, you would see a massive, near-zero desaturation dip. If this would have been the case, then one might have been able to argue that muscle acidity was increasing more rapidly during the actual contraction, as would have been supported by an increase in the rate and level of desaturation from set to set. Thus, failure was actually induce by peripheral mechanisms. However, this was not quite the case. If you look at the last yellow dot on figure 1, you will see desaturation levels hardly dipped. Yet, this was the final that failed to met the velocity standards. If acidity was the culprit, one would have expected to see a larger amount of desaturation, which did not occur .
In conclusion, using small velocity drop offs may be critical in minimizing metabolic fatigue. However, this does not mean exercise does not come without a cost. A lack of reduction in peripheral fatigue may place greater demands on central fatigue. Thus, chronically induced central fatigue may lead to more long term, “overreaching” training effects if not properly monitored. This case study is by no means definitive. Instead, I hope it opens the door the greater discussions as to what fatigue actually is, how we monitor it, and what it means for the development of long term performance.