The mechanical characterization of biological samples is a fundamental issue in biology and related fields, such as tissue and cell mechanics, regenerative medicine and diagnosis of diseases. In this paper, a novel approach for the identification of the stiffness and damping coefficients of biosamples is introduced. According to the proposed method, a MEMS-based microgripper in operational condition is used as a measurement tool. The mechanical model describing the dynamics of the gripper-sample system considers the pseudo-rigid body model for the microgripper, and the Kelvin–Voigt constitutive law of viscoelasticity for the sample. Then, two algorithms based on recursive least square (RLS) methods are implemented for the estimation of the mechanical coefficients, that are the forgetting factor based RLS and the normalised gradient based RLS algorithms. Numerical simulations are performed to verify the effectiveness of the proposed approach. Results confirm the feasibility of the method that enables the ability to perform simultaneously two tasks: sample manipulation and parameters identification.

This paper focuses on the possibility of using a recently fabricated micro gripper for the on line estimation of the mechanical characteristics (damping and elasticity) of a sample pinched by the jaws, with particular reference to biological tissues. A classical on line dynamical parameter estimator is computed for the given system with different estimation computations, and its effectiveness has been verified by numerical simulations. Results confirm the feasibility of a micro-robotic clinical device for surgery use equipped with a tissue recognition ability.

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