Development and validation of dynamic bioenergetic model for intermittent ergometer cycling

Area of Science:

• Exercise Physiology
• Computational Biology
• Sports Science

Background:

• Understanding the body's energy systems is crucial for optimizing athletic performance and training.
• Existing models often simplify the complex interplay between different metabolic pathways during exercise.
• A dynamic bioenergetic model can provide deeper insights into energy supply and demand during physical activity.

Purpose of the Study:

• To develop and validate a comprehensive bioenergetic model.
• To describe the dynamic behavior of alactic, lactic, and aerobic energy supply systems.
• To model the metabolic energy demand from cycling work, ventilation, and metabolite accumulation.

Main Methods:

• Formulated a bioenergetic model as a system of differential equations.
• Employed a non-linear grey-box approach for parameter estimation.
• Utilized power output and aerobic metabolic rate data from cyclists during ergometer trials.

Main Results:

• The model demonstrated good agreement between simulated and measured aerobic metabolic rate (MRae).
• Root mean square error for MRae was 61.9 ± 7.9 W (P2) and 79.2 ± 30.5 W (P3).
• Mean absolute percentage error for MRae was 8.6 ± 1.5% (P2) and 10.6 ± 3.3% (P3).

Conclusions:

• The bioenergetic model shows excellent agreement for predicting MRae during intermittent cycling.
• Validation indicates the model's utility for well-trained male cyclists.
• Reliability for the follow-up trial (P3) showed a notable standard deviation, suggesting areas for refinement.