Non-contact strain measurement in the mouse forearm loading model using digital image correlation (DIC)

Abstract

This study investigates the use of a non-contact method known as digital image correlation (DIC) to measure strains in the mouse forearm during axial compressive loading. A two camera system was adapted to analyze the medial and lateral forearm displacements simultaneously, and the derived DIC strain measurements were compared to strain gage readings from both the ulna and radius. Factors such as region-of-interest (ROI) location, lens magnification, noise, and out-of-plane motion were examined to determine their influence on the DIC strain measurements. We confirmed that our DIC system can differentiate ROI locations since it detected higher average strains in the ulna compared to the radius and detected compressive strains on medial bone surfaces vs. tensile strains on lateral bone surfaces. Interestingly, the DIC method also captured heterogeneity in surface strain fields which are not detectable by strain gage based methods. A separate analysis of the noise intrinsic to the DIC system also revealed that the noise constituted less than 4.5% of all DIC strain measurements. Furthermore, finite element (FE) simulations of the forearm showed that out-of-plane motion was not a significant factor that influenced DIC measurements. Finally, we observed that average DIC strain measurements can be up to 1.5–2 times greater than average strain gage readings on the medial bone surfaces. These findings suggest that strain experienced in the mouse forearm model by loading is better captured through DIC as opposed to strain gages, which as a result of being glued to the bone surface artificially stiffen the bone and lead to an underestimation of the strain response.