Towards High-Accuracy Athletic Injury Predictions Using a First-Principles Modelling Approach: Theory to (Future)...

Area of Science:

• Biomechanics
• Sports Medicine
• Mathematical Modeling

Background:

• Athletic injuries result from tissue damage due to kinetic energy transfer or excessive stress.
• Current definitions lack precise mathematical frameworks for prediction.
• Quantifying tissue damage (D) from 0 (undamaged) to 1 (failure) is crucial.

Purpose of the Study:

• Establish a deterministic mathematical definition for athletic injury.
• Develop probabilistic models for accurate injury risk assessment.
• Identify data-driven windows for athletic injury prevention.

Main Methods:

• Defined athletic injury as damage (D) exceeding a critical threshold (Dc).
• Alternatively defined injury as applied load (L) exceeding critical strength (Sc).
• Utilized probabilistic models to quantify injury likelihood based on load and strength variability.

Main Results:

• Mathematical definitions provide precise frameworks for injury prediction models.
• Probabilistic approaches account for inherent variability in tissue load and strength.
• Accurate variable estimation is key for actionable, data-driven interventions.

Conclusions:

• A deterministic approach offers a precise definition for athletic injury modeling.
• Probabilistic models are necessary to address real-world variability and uncertainty.
• Accurate prediction models are vital for effective, timely athletic injury prevention strategies.