A Vision-Based Methodology to Dynamically Track and Describe Cell Deformation during Cell Micromanipulation

Karimirad, Fatemeh; Shirinzadeh, Bijan; Yan, Wenyi; Fatikow, Sergej

doi:10.1080/15599612.2012.744433

Cited by 15 publications

(3 citation statements)

References 20 publications

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“…SSD Template matching was employed to track the pipettes, and system efficiency was improved by multiple micromanipulators. Karimirad et al [226] presented an active contour-based tracking method for deformable cells during the microinjection. It also provided a precise description of the deformable cells.…”

Section: B Automated Micromanipulationmentioning

confidence: 99%

A Review of Computer Microvision-Based Precision Motion Measurement: Principles, Characteristics, and Applications

Sheng

Pang

et al. 2021

IEEE Trans. Instrum. Meas.

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Micro/nano engineering is an emerging field which enables engineering and scientific discoveries in the microworld. As an effective and powerful tool for automation and manipulation at small scales, precision motion measurement by computer micro-vision is now broadly accepted and widely used in micro/nano engineering. Unlike other measurement methods, the vision-based techniques can intuitively visualize the measuring process with high interactivity, expansibility, and flexibility. This review paper aims to comprehensively present a survey of micro-vision-based motion measurement from the collective experience. Working principles of micro-vision systems are firstly introduced and described, where the hardware configuration, model calibration, and motion measurement algorithms are systematically summarized. The characteristics and performances of different micro-vision-based methods are then analyzed and discussed in terms of measurement resolution, range, degree of freedom, efficiency, and error sources. Recent advances of applications empowered by the developed computer micro-visionbased methods are also presented. The review can be helpful to researchers who engage in the development of micro-vision-based techniques, as well as provide the recent state and tendency for the research community of vision-based measurement, manipulation, and automation at micro/nano scales.

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Section: B Automated Micromanipulationmentioning

confidence: 99%

A Review of Computer Microvision-Based Precision Motion Measurement: Principles, Characteristics, and Applications

Sheng

Pang

et al. 2021

IEEE Trans. Instrum. Meas.

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“…In single cell microinjection, capillary pressure microinjection (CPM) systems are widely utilized to mechanically penetrate the cell membrane [1]. In the process of indenting large spherical cells, the interaction force can be detected by piezoelectric force sensors, enabling force-feedback control to be performed [2,3]. Recent investigations into the micropositioning of samples has demonstrated accurate and efficient placement on micrometre and nanometre scales [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Sensing and Modelling Mechanical Response in Large Deformation Indentation of Adherent Cell Using Atomic Force Microscopy

Shen

Shirinzadeh

Zhong

et al. 2020

Sensors

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The mechanical behaviour of adherent cells when subjected to the local indentation can be modelled via various approaches. Specifically, the tensegrity structure has been widely used in describing the organization of discrete intracellular cytoskeletal components, including microtubules (MTs) and microfilaments. The establishment of a tensegrity model for adherent cells has generally been done empirically, without a mathematically demonstrated methodology. In this study, a rotationally symmetric prism-shaped tensegrity structure is introduced, and it forms the basis of the proposed multi-level tensegrity model. The modelling approach utilizes the force density method to mathematically assure self-equilibrium. The proposed multi-level tensegrity model was developed by densely distributing the fundamental tensegrity structure in the intracellular space. In order to characterize the mechanical behaviour of the adherent cell during the atomic force microscopy (AFM) indentation with large deformation, an integrated model coupling the multi-level tensegrity model with a hyperelastic model was also established and applied. The coefficient of determination between the computational force-distance (F-D) curve and the experimental F-D curve was found to be at 0.977 in the integrated model on average. In the simulation range, along with the increase in the overall deformation, the local stiffness contributed by the cytoskeletal components decreased from 75% to 45%, while the contribution from the hyperelastic components increased correspondingly.

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“…For the first case, the end-effector of a micromanipulator has a mechanical arm connecting it to its base. This type of micromanipulator includes lead-screw driving stages and piezoelectric actuators [1,2,3]. However, the mechanical connection produces frictions, vibration, and backlash that degrade the performance of micromanipulation.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Motion Control of a Magnetically Navigated Microrobotic System

Zhang

Khamesee

2016

Proceedings of the 3rd International Conference of Control, Dynamic Systems, and Robotics (CDSR'16)

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-This paper presents a technology for remotely navigating a magnetized microrobot in three-degree-of-freedom (3-DOF) using magnetic energy. The magnetic energy source is a magnetic drive unit that consists of six iron-core electromagnets, a soft-iron yoke, and a soft-iron pole-piece. The dynamic models of the magnetically navigated microrobot were derived from the magnetic field model in the workspace. An experimental method was applied to define the magnetic field model. Based on the derived dynamic models, a feed-forward plus standard PID controller was used to control the motion of the microrobot with 3-DOF. Experiment was conducted to validate the performance of the proposed controller. The experimental results showed 20µm motion accuracy in 3-DOF in a motion range of 10 × 10 × 30mm 3 .Keywords: Magnetic navigation, Microrobot, Magnetic field, PID plus feedforward controller IntroductionMicromanipulation involves performing tasks using macro scale end-effectors that have micro motion accuracy, and using micro scale end-effectors directly. For the first case, the end-effector of a micromanipulator has a mechanical arm connecting it to its base. This type of micromanipulator includes lead-screw driving stages and piezoelectric actuators [1,2,3]. However, the mechanical connection produces frictions, vibration, and backlash that degrade the performance of micromanipulation. For the second case, an end-effector is remotely manipulated without any mechanical connection to the base of a micromanipulator. This type of micromanipulator is capable of working in hazard and out-of-reach environments. Magnetic levitation micromanipulators, having remotely manipulated micro end-effector and micrometer motion accuracy, are most frequently studied and have promising potential in biomedical applications [4,5,6,7,8].Active magnetic navigation of a microrobot requires a controlled magnetic field source. Generally, electromagnets are used for multi-dimensional manipulation of a microrobot [9,10,11,12]. The magnetic field generated by electromagnets is controlled by a current. The multi-degree of motion freedom of a robot is achieved by setting up special configurations of multi-electromagnets. Since the strength of the magnetic field decays rapidly as the distance from electromagnet increases, an iron-core is commonly used to significantly enhance the magnetic field strength outside the electromagnet. This enhanced magnetic field can then expand the workspace of the microrobot.Modeling the magnetic field in the microrobots workspace is crucial to developing a magnetic navigation system. For systems that have air-core coils and permanent magnets produced magnetic field, analytical methods such as Bio-Savart Law and Amperes Law are applied to find a closed-form magnetic field model. However, for systems that have iron-core electromagnets produced magnetic field, the iron results in high nonlinearity in the whole system. Therefore, it is difficult to find a closed-form for modeling the magnetic field in the workspace. Al...

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A Vision-Based Methodology to Dynamically Track and Describe Cell Deformation during Cell Micromanipulation

Cited by 15 publications

References 20 publications

A Review of Computer Microvision-Based Precision Motion Measurement: Principles, Characteristics, and Applications

A Review of Computer Microvision-Based Precision Motion Measurement: Principles, Characteristics, and Applications

Sensing and Modelling Mechanical Response in Large Deformation Indentation of Adherent Cell Using Atomic Force Microscopy

Modeling and Motion Control of a Magnetically Navigated Microrobotic System

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