title: Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens.
abstract: Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and product development. Stress-strain relationships are typically obtained from mechanical testing data to enable comparative assessment among samples and in some cases identification of constitutive mechanical properties. However, errors may be introduced through the use of average strain measures, as significant heterogeneity in the strain field may result from geometrical non-uniformity of the sample and stress concentrations induced by mounting/gripping of soft tissues within the test system. When strain field heterogeneity is significant, accurate assessment of the sample mechanical response requires measurement of local strains. This study demonstrates a novel biomechanical testing protocol for calculating local surface strains using a mechanical testing device coupled with a high resolution camera and a digital image correlation technique. A series of sample surface images are acquired and then analyzed to quantify the local surface strain of a vascular tissue specimen subjected to ramped uniaxial loading. This approach can improve accuracy in experimental vascular biomechanics and has potential for broader use among other native soft tissues, engineered soft tissues, and soft hydrogel/polymeric materials. In the video, we demonstrate how to set up the system components and perform a complete experiment on native vascular tissue.
authors: Biomedical Engineering Program, University of South Carolina.
authors: Boran
authors: B
authors: Zhou
authors: Department of Mechanical Engineering, University of South Carolina.
authors: Suraj
authors: S
authors: Ravindran
authors: Department of Mechanical Engineering, University of South Carolina.
authors: Jahid
authors: J
authors: Ferdous
authors: Department of Mechanical Engineering, University of South Carolina.
authors: Addis
authors: A
authors: Kidane
authors: Department of Mechanical Engineering, University of South Carolina.
authors: Michael A
authors: MA
authors: Sutton
authors: Biomedical Engineering Program, University of South Carolina; Department of Mechanical Engineering, University of South Carolina; SHAZLY@cec.sc.edu.
authors: Tarek
authors: T
authors: Shazly
mesh_terms: D000818:Animals; D001012:Aorta, Abdominal / Q000033:anatomy & histology / Q000502:physiology; D001696:Biomechanical Phenomena; D001703:Biophysics; D001808:Blood Vessels / Q000033:anatomy & histology / Q000502:physiology*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D013314:Stress, Mechanical; D013499:Surface Properties; D013552:Swine