Three dimensional mechanical modelling and analysis of embryos microinjection.

This research has developed a novel 3D particle based cell model that is able to accurately estimate the membrane deformation and indentation force in bio-micromanipulation of an individual cell, especially embryos microinjection practice

Business During COVID: An IOT Based Automated Sand Truck Management Solution

As a result of the development in computing technologies have begun to believe the human expectations on these needs in the different sort of components. The eSand Transport System with IOT (eSTSI) is a sand transport system designed to provide secure and accurate data such as gross weight with the sand and the truck, viewing the details of the owner when the RFID card is detected, sending alerts through the mobile application from the Firebase by interconnecting with IOT device, viewing the schedule of the selected truck with the data and destination, and displaying the location once the truck is passed the checkpoints. The main functionalities of eSTSI are to identify the truck with the correct information via the RFID card that retrieves the data who has enrolled with the app and stores the data in the firebase. The expected services are aimed to provide by this system

The Design and Development of an Intelligent Atraumatic Laparoscopic Grasper

A key tool in laparoscopic surgery is the grasper, which is the surgeon’s main means of manipulating tissue within the body. However inappropriate use may lead to tissue damage and poor surgical outcomes. This thesis presents a novel approach to the assessment and prevention of tissue damage caused by laparoscopic graspers. The research focusses on establishing typical grasping characteristics used in surgery and thus developing a model of mechanically induced tissue trauma. A review explored the state-of-the-art in devices for measuring surgical grasping, tissue mechanics, and damage quantification to inform the research. An instrumented grasper was developed to characterise typical surgical tasks, enabling the grasping force and jaw displacement to be measured. This device was then used to quantitatively characterise grasper use in an in-vivo porcine model where the device was used to perform organ retraction and manipulation tasks. From this work, the range of forces and the grasping times used in certain tasks were determined and this information was used to guide the rest of the study. The in-vivo investigation highlighted a need for grasping in a controlled environment where the tissue’s mechanical properties could be studied. A grasper test rig was designed and developed to provide automated controlled grasping of ex-vivo tissue. This allowed the mechanical properties of tissue to be determined and analysed for indications of tissue damage. A series of experimental studies were conducted with this system which showed how the mechanical response of tissue varies depending on the applied grasping force characteristics, and how this is indicative of tissue damage through comparison to histological analysis. These data were then used to develop a model which predicts the likelihood and severity of tissue damage during grasping, based on the input conditions of grasping force and time. The model was integrated into the instrumented grasper system to provide a tool which could enable real-time grading and feedback of grasping during surgery, or be used to inform best practice in training scenarios

Characterisation and State Estimation of Magnetic Soft Continuum Robots

Minimally invasive surgery has become more popular as it leads to less bleeding, scarring, pain, and shorter recovery time. However, this has come with counter-intuitive devices and steep surgeon learning curves. Magnetically actuated Soft Continuum Robots (SCR) have the potential to replace these devices, providing high dexterity together with the ability to conform to complex environments and safe human interactions without the cognitive burden for the clinician. Despite considerable progress in the past decade in their development, several challenges still plague SCR hindering their full realisation. This thesis aims at improving magnetically actuated SCR by addressing some of these challenges, such as material characterisation and modelling, and sensing feedback and localisation. Material characterisation for SCR is essential for understanding their behaviour and designing effective modelling and simulation strategies. In this work, the material properties of commonly employed materials in magnetically actuated SCR, such as elastic modulus, hyper-elastic model parameters, and magnetic moment were determined. Additionally, the effect these parameters have on modelling and simulating these devices was investigated. Due to the nature of magnetic actuation, localisation is of utmost importance to ensure accurate control and delivery of functionality. As such, two localisation strategies for magnetically actuated SCR were developed, one capable of estimating the full 6 degrees of freedom (DOFs) pose without any prior pose information, and another capable of accurately tracking the full 6-DOFs in real-time with positional errors lower than 4~mm. These will contribute to the development of autonomous navigation and closed-loop control of magnetically actuated SCR

Modelling a precision loadcell using neural networks for vision-based force measurement in cell micromanipulation

This paper presents a vision-based method to model a precision loadcell with artificial neural networks. The proposed model is used for measuring the applied force to a spherical biological cell during micromanipulation processes. The devised vision-based method is most useful where force feedback is required while integrating a force sensor into a cell micromanipulation setup is a challenging job. The proposed neural network model is used in conjunction with a methodology to track and characterize the cell deformation by extracting a geometric feature referred to as the 'dimple angle' directly from images of the cell micromanipulation process. The neural network is trained and used for the experimental data of zebrafish embryos micromanipulation. However, the proposed neural network is applicable for indentation of any other spherical elastic object. The results demonstrate the capability of the proposed method. The outcomes of this study could be useful for measuring force in biological cell microinjection processes such as injection of the mouse oocyte/embryo

Nanomaterials for Biomedical and Biotechnological Applications

The need for constant improvement to reach a high standard of safety and to make nanomaterials accessible for marketing has generated a considerable number of scientific papers that highlight new important aspects to be considered, such as synthesis, stability, biocompatibility, and easy manipulation. In order to provide a comprehensive update on the latest discoveries concerning nanomaterials, this reprint presents 14 scientific papers, 10 research articles and 4 reviews, that deal with biomedical and biotechnological applications of nanomaterials