Full-field strain measurements on medical devices using digital image correlation: Considerations and practical examples

Area of Science:

• Biomedical Engineering
• Materials Science
• Mechanical Engineering

Background:

• Direct stress and strain measurements are crucial for implantable medical device design and validation.
• Current methods for acquiring these measurements on medical devices are limited.
• Optical digital image correlation (DIC) offers a promising non-contact approach for full-field strain analysis.

Purpose of the Study:

• To investigate the feasibility of using optical DIC for full-field strain measurements on medical devices.
• To evaluate various speckle pattern application techniques for DIC analysis on medical device materials.
• To demonstrate the capability of DIC in characterizing strain behavior, including phase transformations, in medical devices.

Main Methods:

• Exploration of multiple speckle pattern application methods: aerosol painting, transfer papers, airbrushing (low/high pressure, different paints), graphite powder deposition, and microstamping.
• Comparative analysis of speckle pattern quality across different scales (millimeter and sub-millimeter).
• Application of DIC to measure full-field strains on nitinol-based medical device components (wire, Z-specimens, stent rings) under bending loads.

Main Results:

• High-pressure airbrushing produced optimal speckle patterns at the millimeter scale.
• Monodisperse graphite powder and microstamping yielded superior speckle patterns at the sub-millimeter scale.
• DIC successfully identified Lüders-like phase transformation bands in nitinol components under bending, demonstrating its ability to capture complex deformation phenomena.

Conclusions:

• Optical DIC is a feasible technique for direct, full-field strain measurement on actual medical devices.
• The study provides guidance on selecting appropriate speckle pattern methods based on the desired scale of analysis.
• Findings support the use of DIC for enhancing medical device design, durability assessment, and computational modeling.