Soft Tissue Mechanics: A Key to Predicting How Our Bodies Behave - By Sarah Iaquinta

When you bend your knee, stretch out your arm, or even just give someone a hug, you are relying on soft tissues, muscles, tendons, ligaments, and a whole network of structures that keep us moving.

Unlike steel beams or concrete walls, these tissues do not follow simple, predictable rules. They stretch, stiffen, relax, and adapt depending on how they are loaded.

That is exactly why the study of soft tissue mechanics is so captivating: it is about figuring out how living materials really behave.

In recent years, researchers have taken big steps forward in this field. Instead of treating tissues like oversized rubber bands, we now have models that reflect their true complexity. Hyperelastic models help us describe how tissues stretch well beyond what “normal” materials could handle, while viscoelastic models explain why tissues do not just snap back instantly but take time to settle after being stretched.

Testing these ideas has also become more sophisticated. Take digital image correlation (DIC), for example. It is a technique widely used in materials science to measure strain fields with great accuracy, and it has also become increasingly common in biomechanics. The principle is simple: high-resolution cameras track tiny surface markers on a sample as it deforms, giving researchers a full-field map of strains in real time. Applying it to biological tissues, however, comes with specific challenges—like accounting for their non-uniform structure, hydration, or transparency. Still, it is proving to be a powerful tool to bridge the gap between experimental data and computational models.

Displacement field during a uniaxial tensile test on porcine anal mucosa, obtained using Digital Image Correlation (LMGC_DIC software).

This is not just theory. A great example is the PELVITRACK project, which focuses on pelvic tissues during childbirth. The goal is simple but ambitious: To understand how these tissues deform and use that knowledge to prevent pelvic trauma. Here, soft tissue mechanics goes beyond equations—it becomes a tool for better diagnosis, prevention, and care.

And the road ahead? It looks very promising. With the rise of computational science, data science, and machine learning, we are moving towards the idea of patient-specific digital twins of tissues. These virtual replicas could forecast how a person’s tissues respond to stress or injury and even let health care professionals test out treatment strategies before applying them in practice. Such advances pave the way for personalised medicine, where care is tailored not just to the average patient, but to each individual’s unique tissue properties.

For students and early-career researchers, this is an exciting moment: biology, engineering, and data are coming together in ways that can make a real difference in people’s lives.