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

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

Learning Micromanipulation, Part 1: An Approach Based on Multidimensional Ability Inventories and Text Mining.

In the last decades, an effort has been made to improve the efficiency of high-level and academic education players. Nowadays, students’ preferences and habits are continuously evolving and so the educational institutions deal with important challenges, such as not losing attractiveness or preventing early abandonment during the programs. In many countries, some important universities are public, and so they receive national grants that are based on a variety of factors, on which the teaching efficiency has a great impact. This contribution presents a method to improve students commitment during traditional lessons and laboratory tests. The idea consists in planning some activities according to the students’ learning preferences, which were studied by means of two different approaches. The first one was based on Gardner’s multiple intelligence inventory, which is useful to highlight some peculiar characteristics of the students on the specific educational field. In the second method, direct interviews, voice recognition, and text mining were used to extract some interesting characteristics of the group of students who participated in the projects. The methods were applied in May 2018 to the students attending the course of Micro-Nano Sensors and Actuators for the postgraduate academic program dedicated to Industrial Nanotechnologies Engineering of the University of Rome La Sapienza. The present paper represents the first part of the investigation and it is dedicated essentially to the adopted methods. The second part of the work is presented in the companion paper dedicated to the presentation of the practical project that the students completed before the exam

Computer Vision Measurements for Automated Microrobotic Paper Fiber Studies

The mechanical characterization of paper fibers and paper fiber bonds determines the key parameters affecting the mechanical properties of paper. Although bulk measurements from test sheets can give average values, they do not yield any real fiber-level data. The current, state-of-the-art methods for fiberlevel measurements are slow and laborious, requiring delicate manual handling of microscopic samples. There are commercial microrobotic actuators that allow automated or tele-operated manipulation of microscopic objects such as fibers, but it is challenging to acquire the data needed to guide such demanding manipulation. This thesis presents a solution to the illumination problem and computer vision algorithms for obtaining the required data. The solutions are designed for a microrobotic platform that comprises actuators for manipulating the fibers and one or two microscope cameras for visual feedback.The algorithms have been developed both for wet fibers, which can be treated as 2D objects, and for dry fibers and fiber bonds, which are treated as 3D objects. The major innovations in the algorithms are the rules for the micromanipulation of the curly fiber strands and the automated 3D measurements of microscale objects with random geometries. The solutions are validated by imaging and manipulation experiments with wet and dry paper fibers and dry paper fiber bonds. In the imaging experiments, the results are compared with the reference data obtained either from an experienced human or another imaging device. The results show that these solutions provide morphological data about the fibers which is accurate and precise enough to enable automated fiber manipulation. Although this thesis is focused on the manipulation of paper fibers and paper fiber bonds, both the illumination solution and the computer vision algorithms are applicable to other types of fibrous materials

Micro/nanoscale magnetic robots for biomedical applications

Magnetic small-scale robots are devices of great potential for the biomedical field because of the several benefits of this method of actuation. Recent work on the development of these devices has seen tremendous innovation and refinement toward ​improved performance for potential clinical applications. This review briefly details recent advancements in small-scale robots used for biomedical applications, covering their design, fabrication, applications, and demonstration of ability, and identifies the gap in studies and the difficulties that have persisted in the optimization of the use of these devices. In addition, alternative biomedical applications are also suggested for some of the technologies that show potential for other functions. This study concludes that although the field of small-scale robot research is highly innovative ​there is need for more concerted efforts to improve functionality and reliability of these devices particularly in clinical applications. Finally, further suggestions are made toward ​the achievement of commercialization for these devices

Measurement of Z-Directional Individual Fibre-Fibre Bond Strength and Microfibril Angle Using Microrobotics

The use of microrobotics in high throughput and precise characterization of objects at microscale has been noticeably increased during recent years. Microrobotics has provided a significant added value to multiple realms e.g. biomedical research, bio-based industry, microassembly of miniature products, etc. Recently, the use of microrobotic technology in paper industry has been also commenced for measuring properties at the single fibre level. There is a large interest in the measurement of different loading modes of individual fibre-fibre bonds in pulp and paper/board industry. Among the four different modes of loading, it would be desirable for papermaking companies and paper converting companies to obtain the Z-directional strength of pulp and paper. Indeed, the Z-directional properties affect compressive properties, and accordingly the performance of structural paperboard products. Several methods have been developed to measure the Z-directional strength at a handsheet level; however, there is not any reported device capable of the Z-directional fibre-fibre bond strength measurement at a fibre level. This thesis work presents a novel method for the experimental evaluation of the Z-directional bond strength using microrobotics and a Polyvinylidene fluoride (PVDF) film microforce sensor. Due to the special dynamics of PVDF microforce sensors, the effect of the deformation rate on the performance of the sensor is studied. The Z-directional fibre-fibre bond strength experiments have been performed successfully for unrefined and refined bleached softwood Kraft pulp fibres. Besides, paper scientists are interested in microfibril angle changes during and after application of the Z-directional force. Indeed, there is interest in simultaneous measurement of microfibril angle and mechanical properties such as Z-directional bond strength. To address this need, a microfibril angle measurements system based on microscopic transmission ellipsometry is developed and integrated to the microrobotic platform. The results from both Z-directional bond strength and microfibril angle measurement are promising. In summary, the first concept for simultaneous measurement of microfibril angle and mechanical properties such as Z-directional bond strength at the individual fibre level is developed during this thesis work which has a high practical impact on the fibre characterization research field

MICROMANIPULATOR-RESONATOR SYSTEM FOR SELECTIVE WEIGHING OF INDIVIDUAL MICROPARTICLES

Over the past decade, MEMS-based cantilever sensors have been widely used in the detection of biomolecules, environmental pollutants, chemicals and pathogens. Cantilever-based sensors rely on attachment of target entities on their surface. The attachment causes either change in surface stress or resonance frequency of the cantilever, which is detected using various schemes that range from optical to piezoelectric. The majority of these sensors rely on probabilistic attachment of multiple target entities to the sensor surface. This introduces uncertainties since the location of the adsorbed target entity can modify the signal generated by the sensor. In addition, it does not allow the measurement of individually selected target entities. The goal of this dissertation is to exploit the cantilever-based sensors\u27 mass sensing capability to develop a supermarket weight scale for the micro world: a scheme that can enable the user to pick an individual target entity and weigh only that particular entity by precisely positioning it on a micro- weight scale

Conceptual design of a gripper for a first-aid robot

First aid is the tentative care for anyone who is injured or ill before definitive medical care arrives. Advancements in technology offer robots the potential to be used extensively in first aid to replace human workers. Currently, many elderly people live alone and absence of care can increase risks of illness- or injury-induced unconsciousness. Due to this, it would be useful to investigate if robots could be employed to perform first-aid care. However, their application in aiding humans in such circumstances is still relatively rare due to complexities concerning safety, communication and ability to interact with humans. This thesis is part of a project to design a first-aid robot to manipulate an unconscious human from any position to the recovery position. The only direct contact with human is through gripper of the robot. An attempt to develop a conceptual design of cost-effective grippers has been undertaken. This will enable a robot to perform the handling and manipulation of human segments to achieve the recovery position. For the purpose of robotic application, a research into the feasibility of human body manipulation is being conducted. Initial stage of research is to identify the limit of physical robot-human interaction; the biomechanical characteristics of human body that decide these limits and essential gripper specifications required to theoretically carry out robot-human interactions to those limits. The research is focused on the geometric properties of various human body parts, defined as body segments, and the minimum gripper specification needed to manipulate these segments. A novel systematic design approach has been applied to the gripper by utilizing a design tool known as the Theory of Inventive Problem Solving (TRIZ). Results ii obtained from this study have substantiated design work to derive an enhanced design solution, which will enable the gripper to perform delicate tasks. The gripper‟s main priorities have been identified and concluded that fundamental issues are: safely engaging human segments and preventing pain exceeding the recommended pain threshold. This work could form the basis of developing and integrating the First Aid Robotic System (FAROS) and pave a way for further developments and innovations