Gauging muscle tone with ventilation
In Marius Bakken's book and interviews, he frequently discusses muscle tone/state as the best way to assess daily condition, but notes that there is no easy, objective way to measure it. For those that are interested in this subject, I think I have discovered a method to reliably track it (indirectly) - by measuring minute ventilation during exercise.
I first started using minute ventilation back in September as a method to control intensity. And although on most days, my ventilation values are consistent at the same pace, occassionally, my ventilation will spike well above normal levels. At first I dismissed this as random noise, but then I started noticing a pattern - these spikes were often correlated to days where my condition was impaired, such as after a hard workout or a heavy squat day.
For example, attached are two graphs plotting my runs from 4/1-8/1. The top graph plots each of these runs by pace (x-axis) and ventilation (y-axis). The bottom graph plots the same runs by date (x-axis) and deviation from my "average" ventilation values at their respective paces (y-axis) - where red bars indicate runs above my average and green bars indicate runs below my average.
The red circled areas highlight two periods where I experienced a cluster of very high ventilation values (the faint blue shaded area near the center line is 1 standard of deviation from my average), which coincide with the time where my condition was at its worst - the first period was during my double threshold experiment, and the second period was during my week long "vacation" which involved carrying around an 8mo old for miles every day at places like disneyland turning my legs into lead.
Given this pattern, I decided to research why this was happening, and it turns out there is a physiological basis for ventilation significantly increasing when your muscles are damaged, even when lactate concentrations remain normal - When your muscles are damaged, they can't contract with the same amount of force as they ordinarily do. When your muscles can't contract with ordinary force, due to the size principle, they must recruit additional fast-twitch fibers to produce the same amount of power. And when your body recruits a greater percentage of fast twitch fibers for the same power output, it increases your relative CO2 production (which correlates to ventilation) due to 3 primary factors:
(1) Fast twitch fibers are less efficient from an oxygen utilization standpoint compared to slow twitch fibers, meaning they require more ATP/oxygen to produce the same amount of power, which increases CO2.
(2) Fast twitch fibers highly prefer glucose over fat relative to slow twitch fibers and oxidizing glucose produces more CO2 compared to fat.
(3) Fast twitch fibers generally have fewer and smaller mitochondria compared to slow twitch fibers which causes them to be more prone to producing energy through anaerobic glycolysis, resulting in more H+ accumulation, which generates more CO2.
So why can't lactate be used to reliably assess muscle state? For two main reasons: (a) Lactate doesn't cleanly track metabolic CO2 production (#1 and 2 above) because fat oxidation doesn't produce lactate and glucose oxidation only produces a small net amount. (b) Although lactate does track H+ accumulation (#3 above), in the moderate domain, by the time an athlete takes a lactate concentration sample in the ear or finger, most/all of that excess H+/lactate is recylced in the body.
It is true that your lactate concentrations should also be higher than normal in the heavy/severe domains when your muscles are impaired, but due to how lactate concentration is measured, you won't know this until the middle or end of your workout. And personally, I do not alter any of my workouts based on poor condition - I power through them, with the sole exception being when I cross my VT2. But I do heavily modulate the duration/pace of virtually all of my cooldowns and easy runs based on my present condition.
Having tracked over 1,000 runs using ventilation, I now use it exclusively to assess condition/fatigue, where I previously used a number of different tools such as whoop, garmin, strava, intervalsicu etc. The issue with these sorts of algorithmic fatigue trackers is that they primarily rely on external metrics, which is like trying to manage one's diabetes by counting macros. In contrast, tracking ventilation is like using a glucose monitor because it tells you what is happening internally at that given moment.