A model-based estimation of critical torques reduces the experimental effort compared to conventional testing

Area of Science:

• Exercise Physiology
• Biomechanics
• Human Performance Analysis

Background:

• Critical torque (CT) is a crucial fatigue threshold in exercise physiology.
• Accurate CT estimation is vital for performance analysis, prediction, and optimization.
• Current methods for CT estimation can be experimentally demanding.

Purpose of the Study:

• To develop a model-based approach to reduce experimental effort in estimating critical torque (CT).
• To apply this approach to both sustained and intermittent isometric contractions.
• To optimize the estimation process for greater efficiency.

Main Methods:

• Utilized a phenomenological model of maximum voluntary isometric contraction (MVIC) torque.
• Formulated CT estimation as a parameter estimation problem.
• Computed optimized testing sessions to minimize statistical uncertainty and experimental effort.

Main Results:

• Estimated CT for elbow flexors in sustained isometric contractions at 28% of baseline MVIC.
• Estimated CT for intermittent isometric contractions (3s on, 2s off) at 41% of baseline MVIC.
• Demonstrated that a single optimized testing session is sufficient for accurate CT estimation.

Conclusions:

• The proposed model-based approach significantly reduces the experimental effort required for CT estimation.
• This method provides a more efficient way to determine critical torque for various contraction types.
• The findings have implications for optimizing training and performance protocols.