Bone strain gage data and theoretical models of functional adaptation

Area of Science:

• Biomechanics
• Orthopedics
• Computational Biology

Background:

• In vivo strain gage implantation on bone is crucial for understanding bone loading, growth, and adaptation.
• Existing experimental data lacks integration with theoretical bone adaptation models.
• Bridging experimental measurements and computational modeling is essential for advancing bone adaptation research.

Purpose of the Study:

• To present methods for analyzing bone strain gage recordings within computational modeling frameworks.
• To introduce a novel parameter, energy equivalent strain, for quantifying cyclic strain magnitudes.
• To develop a concept of daily strain stimulus for bone adaptation analysis.

Main Methods:

• Analysis of bone rosette strain gage recordings.
• Application of strain energy density-based computational modeling and remodeling theories.
• Introduction of "energy equivalent strain" as a scalar measure.
• Development of the "daily strain stimulus" concept.

Main Results:

• A framework for analyzing in vivo bone strain data using computational models is established.
• Energy equivalent strain provides a unified measure of cyclic strain.
• The daily strain stimulus concept offers a new perspective on bone adaptation drivers.
• The approach is successfully applied to analyze historical human tibia loading data.

Conclusions:

• The proposed methods enhance the integration of experimental strain data with computational bone adaptation models.
• Energy equivalent strain and daily strain stimulus are valuable new parameters for biomechanical analysis.
• This approach facilitates a deeper understanding of bone's response to mechanical loading.
• The study provides a robust methodology for future in vivo bone loading research.