Soft tissue deformation modelling forms the basis of development of surgical simulation,
surgical planning and robotic-assisted minimally invasive surgery. This paper presents
a new methodology for modelling of soft tissue deformation based on reaction-diffusion
mechanics via neural dynamics. The potential energy stored in soft tissues due to
a mechanical load to deform tissues away from their rest state is treated as the equivalent
transmembrane potential energy, and it is distributed in the tissue masses in the
manner of reaction-diffusion propagation of nonlinear electrical waves. The reaction-diffusion
propagation of mechanical potential energy and nonrigid mechanics of motion are combined
to model soft tissue deformation and its dynamics, both of which are further formulated
as the dynamics of cellular neural networks to achieve real-time computational performance.
The proposed methodology is implemented with a haptic device for interactive soft
tissue deformation with force feedback. Experimental results demonstrate that the
proposed methodology exhibits nonlinear force-displacement relationship for nonlinear
soft tissue deformation. Homogeneous, anisotropic and heterogeneous soft tissue material
properties can be modelled through the inherent physical properties of mass points.