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Micromanipulation and Biosensing: Emerging Technologies and Applications

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Dear Colleagues,

Micromanipulation and biosensing are two rapidly growing fields that have significant potential to revolutionize various industries such as healthcare, biotechnology, and nanotechnology. This Special Issue aims to showcase the latest advances in these fields and their applications.

One of the key topics covered in the Special Issue is microrobotics, which involves the design and fabrication of micro- and nano-scale robots capable of performing a variety of tasks. This includes robots that can be used for drug delivery, tissue engineering, and even environmental monitoring.

Another focus of the Special Issue is on biosensors, which are devices that can detect and measure biological or chemical substances in a sample. Biosensors have significant applications in medical diagnostics, environmental monitoring, and food safety. The Special Issue also features the advanced development of novel biosensors and their integration with microfluidics and microrobotics.

Furthermore, this Special Issue includes manuscripts on biomanipulation, which involves the manipulation of biological cells and tissues at the micro- and nanoscale. This includes techniques such as optical trapping, magnetic manipulation, and electrophoresis, and their various applications such as cell sorting, tissue engineering, and drug discovery.

Prof. Dr. Yongjun Lai
Dr. Carlos Escobedo
Guest Editors

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Keywords

micromanipulation
sensors
MEMS
biosensing

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0 pages, 13433 KiB

Open AccessArticle

Development of a Large-Range XY-Compliant Micropositioning Stage with Laser-Based Sensing and Active Disturbance Rejection Control

by Ashenafi Abrham Kassa, Bijan Shirinzadeh, Kim Sang Tran, Kai Zhong Lai, Yanling Tian, Yanding Qin and Huaxian Wei

Sensors 2024, 24(2), 663; https://doi.org/10.3390/s24020663 - 20 Jan 2024

Viewed by 775

Abstract

This paper presents a novel design and control strategies for a parallel two degrees-of-freedom (DOF) flexure-based micropositioning stage for large-range manipulation applications. The motion-guiding beam utilizes a compound hybrid compliant prismatic joint (CHCPJ) composed of corrugated and leaf flexures, ensuring increased compliance in primary directions and optimal stress distribution with minimal longitudinal length. Additionally, a four-beam parallelogram compliant prismatic joint (4BPCPJ) is used to improve the motion decoupling performance by increasing the off-axis to primary stiffness ratio. The mechanism’s output compliance and dynamic characteristics are analyzed using the compliance matrix method and Lagrange approach, respectively. The accuracy of the analysis is verified through finite element analysis (FEA) simulation. In order to examine the mechanism performance, a laser interferometer-based experimental setup is established. In addition, a linear active disturbance rejection control (LADRC) is developed to enhance the motion quality. Experimental results illustrate that the mechanism has the capability to provide a range of 2.5 mm and a resolution of 0.4 μm in both the X and Y axes. Furthermore, the developed stage has improved trajectory tracking and disturbance rejection capabilities. Full article

(This article belongs to the Special Issue Micromanipulation and Biosensing: Emerging Technologies and Applications)

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17 pages, 22863 KiB

Open AccessArticle

Neuron Contact Detection Based on Pipette Precise Positioning for Robotic Brain-Slice Patch Clamps

by Ke Li, Huiying Gong, Jinyu Qiu, Ruimin Li, Qili Zhao, Xin Zhao and Mingzhu Sun

Sensors 2023, 23(19), 8144; https://doi.org/10.3390/s23198144 - 28 Sep 2023

Cited by 1 | Viewed by 1090

Abstract

A patch clamp is the “gold standard” method for studying ion-channel biophysics and pharmacology. Due to the complexity of the operation and the heavy reliance on experimenter experience, more and more researchers are focusing on patch-clamp automation. The existing automated patch-clamp system focuses on the process of completing the experiment; the detection method in each step is relatively simple, and the robustness of the complex brain film environment is lacking, which will increase the detection error in the microscopic environment, affecting the success rate of the automated patch clamp. To address these problems, we propose a method that is suitable for the contact between pipette tips and neuronal cells in automated patch-clamp systems. It mainly includes two key steps: precise positioning of pipettes and contact judgment. First, to obtain the precise coordinates of the tip of the pipette, we use the Mixture of Gaussian (MOG) algorithm for motion detection to focus on the tip area under the microscope. We use the object detection model to eliminate the encirclement frame of the pipette tip to reduce the influence of different shaped tips, and then use the sweeping line algorithm to accurately locate the pipette tip. We also use the object detection model to obtain a three-dimensional bounding frame of neuronal cells. When the microscope focuses on the maximum plane of the cell, which is the height in the middle of the enclosing frame, we detect the focus of the tip of the pipette to determine whether the contact between the tip and the cell is successful, because the cell and the pipette will be at the same height at this time. We propose a multitasking network CU-net that can judge the focus of pipette tips in complex contexts. Finally, we design an automated contact sensing process in combination with resistance constraints and apply it to our automated patch-clamp system. The experimental results show that our method can increase the success rate of pipette contact with cells in patch-clamp experiments. Full article

(This article belongs to the Special Issue Micromanipulation and Biosensing: Emerging Technologies and Applications)

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