Next Article in Journal
Effects of Off-Plane Deformation and Biased Bi-Axial Pre-Strains on a Planar Contractile Dielectric Elastomer Actuator
Next Article in Special Issue
Mechanical Response of Four-Bar Linkage Microgrippers with Bidirectional Electrostatic Actuation
Previous Article in Journal
Implementation of Soft-Lithography Techniques for Fabrication of Bio-Inspired Multi-Layer Dielectric Elastomer Actuators with Interdigitated Mechanically Compliant Electrodes
Previous Article in Special Issue
Preparing and Mounting Polymer Nanofibers onto Microscale Test Platforms
Open AccessArticle

Recursive Least Squares Filtering Algorithms for On-Line Viscoelastic Characterization of Biosamples

1
Department of Computer, Control and Management Engineering Antonio Ruberti, Sapienza University of Rome, Via Ariosto, 25, 00185 Rome, Italy
2
University of Rome Niccolò Cusano, Via Don Carlo Gnocchi, 3, 00166 Rome, Italy
*
Author to whom correspondence should be addressed.
Actuators 2018, 7(4), 74; https://doi.org/10.3390/act7040074
Received: 31 August 2018 / Revised: 11 October 2018 / Accepted: 15 October 2018 / Published: 22 October 2018
(This article belongs to the Special Issue Micromanipulation)
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. View Full-Text
Keywords: micromanipulation; microgripper; biological samples analysis; visco-elastic characteristic measurement; dynamic parameters estimation micromanipulation; microgripper; biological samples analysis; visco-elastic characteristic measurement; dynamic parameters estimation
Show Figures

Figure 1

MDPI and ACS Style

Di Giamberardino, P.; Aceto, M.L.; Giannini, O.; Verotti, M. Recursive Least Squares Filtering Algorithms for On-Line Viscoelastic Characterization of Biosamples. Actuators 2018, 7, 74.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop