One of the great problems that training has today is to measure the effect that a stimulus has on the body.
For doing so, we can measure the fatigue we have accumulated. The body responds to stimulus by adapting to them, and this is how we gain strength.
But, how do we know what stimulus we have given to the body?
If we could measure it, we could get to know what is the best stimulus to achieve our goals. The speed of a lift allows us to know accurately what is the stimulus that we have given to the body.
What is fatigue?
The involuntary and inevitable reduction of the force applied after an effort. (Enoka & Stuart, 1992).
The mean velocity of a lift under the same load decreases as we train, we are no longer able to apply so much force.
The loss of velocity, It is a good expression of fatigue that occurs in a workout. (Gonzalez-Badillo, Sanchez-Medina, Pareja-Blanco, & Rod riguez-Rosell, 2017)
Then, if we measure the velocity of execution of the fastest repetition (which is where we apply more force), and the slowest (which is where the least force is applied), knowing that we have done all the reps at the maximum velocity , we can have a reference value of what stimulus we have given to the body.
For example, in a set of 8 reps in bench press, if my first repetition was at 0.65 m/s and my last repetition at 0.4 m/s, making a simple rule of three, I know I have lost 39 % of the execution velocity, also known as 39% of inter-set fatigue.
The science behind the measurement of fatigue
Today it is demonstrated that this loss of velocity is related to changes in some indicators of fatigue in our body, to be more specific: lactate and ammonium.
In a classic paper it was shown that the average velocity loss during three sets had a very high correlation (for the squat r=0.97, and for the bench r=0, 95) with the post-exercise lactate peak (Sanchez-Medina & Gonzalez-Badillo, 2011).
What does this mean? We know that lactate is an indicator of fatigue, because it is shown that it increases according to fatigue.
It is not the cause of fatigue, but we know that as intensity increases, lactate increases in our body.
So if it has been shown that the higher the velocity loss, the higher the post-exercise lactate peak, means that the % velocity lost is a very good way to measure the real fatigue.
What variables do we measure to quantify fatigue?
Inter-fatigue: % of fatigue that we have accumulated in an exercise. If the fastest repetition is 0.4 m/s and the slowest 0.3 m/s, we will have lost 25% of velocity.
In the study mentioned before, they also realized that lactate and ammonium levels did not go really high until more than the half of the possible reps during a set were performed.
Which means, that probably, if we work with those volumes, the recovery will be faster. This does not mean that it is the optimal, but it is a point to take into account to include work that does not produce much fatigue to our body.
1.- The first repetition, or the fastest of the series, is very important, since it indicates to us what intensity we are working with, it will also serve as a reference to know how much we have fatigued, when we lose velocity due to fatigue.
2.- Velocity loss is a great way to quantify fatigue, since it has a very high correlation with post-exercise lactate peak, a physiological indicator of fatigue.
Through Vitruve encoder we can modify and establish a velocity loss as a target. Instantly we can know when we reach that velocity. So we could stop the training, modify the load or modify the number of repetitions to achieve the perfect stimulus for that training.
Gonzalez-Badillo, J., Sanchez-Medina, L., Pareja-Blanco, F., & Rodríguez-Rosell, D. (2017). La velocidad de ejecución como referencia para la programación, control y evaluación del entrenamiento de fuerza.
Hirvonen, J, Nummela, A, Rusko, H, Rehunen, S, Härkönen, M, (1992) Fatigue and changes of ATP, creatine phosphate, and lactate during the 400-m sprint. Canadian journal of sport sciences 17 (2) 141-4
Sánchez-Medina, Luis, González-Badillo, J. J. (2011) Velocity loss as an indicator of neuromuscular fatigue during resistance training Medicine & Science in Sports & ExerciseFebruary issue 1725-34
Enoka, R M, Stuart, D G (1992) Neuriobiology of muscle fatigue Journal of applied physiology 72 (5) 1631-48