Proposal and validation of mathematical model for resistance training

Abstract

A set of mathematical models for resistance training (RT model) with repeated dynamic and voluntary activations of knee extensor muscles was proposed and validated. RT model predicts muscle activity, fatigue and recovery, and can be used to predict the mechanical impulses identified in different muscle fiber types. Several resistance training program variables (e.g. load, velocity, number of sets, and duration of rest intervals) were addressed in this study. Experimental data from six subjects were taken under several different training protocols. For the protocols studied, the model precisely predicted the maximum number of repetitions during knee extension resistance exercise (R2 = 0.87). This study demonstrates the applicability of the first simple mathematical model for voluntary dynamic exercise of knee extensor muscles. The developed model calculates the mechanical impulse of fast twitch fiber for the selected protocols. For instance, the model shows high intensity training tends to induce more fast-twitch fiber recruitment than that in low intensity training in the case of non-failure. This model is expected to help in understanding how impulses of different fiber types contribute and affect training.

Keywords

• training variable
• mathematical modeling
• muscle fiber recruitment
• repetition maximum