Haptic technology for micro-robotic cell injection training systems — a review

Currently, the micro-robotic cell injection procedure is performed manually by expert human bio-operators. In order to be proficient at the task, lengthy and expensive dedicated training is required. As such, effective specialized training systems for this procedure can prove highly beneficial. This paper presents a comprehensive review of haptic technology relevant to cell injection training and discusses the feasibility of developing such training systems, providing researchers with an inclusive resource enabling the application of the presented approaches, or extension and advancement of the work. A brief explanation of cell injection and the challenges associated with the procedure are first presented. Important skills, such as accuracy, trajectory, speed and applied force, which need to be mastered by the bio-operator in order to achieve successful injection, are then discussed. Then an overview of various types of haptic feedback, devices and approaches is presented. This is followed by discussion on the approaches to cell modeling. Discussion of the application of haptics to skills training across various fields and haptically-enabled virtual training systems evaluation are then presented. Finally, given the findings of the review, this paper concludes that a haptically-enabled virtual cell injection training system is feasible and recommendations are made to developers of such systems

Virtual reality training for micro-robotic cell injection

This research was carried out to fill the gap within existing knowledge on the approaches to supplement the training for micro-robotic cell injection procedure by utilising virtual reality and haptic technologies

Vascular neurosurgery simulation with bimanual haptic feedback

International audienceVirtual surgical simulators face many computational challenges: they need to provide biophysical accuracy, realistic feed-backs and high-rate responses. Better biophysical accuracy and more realistic feed-backs (be they visual, haptic.. .) induce more computational footprint. State-of-the-art approaches use high-performance hardware or find an acceptable trade-off between performance and accuracy to deliver interactive yet pedagogically relevant simulators. In this paper, we propose an interactive vascular neurosurgery simulator that provides bi-manual interaction with haptic feedback. The simulator is an original combination of states-of-the-art techniques that allows visual realism, bio-physical realism, complex interactions with the anatomical structures and the instruments and haptic feedback. Training exercises are also proposed to learn and to perform the different steps of intracranial aneurysm surgery (IAS). We assess the performance of our simulator with quantitative performance benchmarks and qualitative assessments of junior and senior clinicians

Interactivity:the missing link between virtual reality technology and drug discovery pipelines

The potential of virtual reality (VR) to contribute to drug design and development has been recognised for many years. Hardware and software developments now mean that this potential is beginning to be realised, and VR methods are being actively used in this sphere. A recent advance is to use VR not only to visualise and interact with molecular structures, but also to interact with molecular dynamics simulations of 'on the fly' (interactive molecular dynamics in VR, IMD-VR), which is useful not only for flexible docking but also to examine binding processes and conformational changes. iMD-VR has been shown to be useful for creating complexes of ligands bound to target proteins, e.g., recently applied to peptide inhibitors of the SARS-CoV-2 main protease. In this review, we use the term 'interactive VR' to refer to software where interactivity is an inherent part of the user VR experience e.g., in making structural modifications or interacting with a physically rigorous molecular dynamics (MD) simulation, as opposed to simply using VR controllers to rotate and translate the molecule for enhanced visualisation. Here, we describe these methods and their application to problems relevant to drug discovery, highlighting the possibilities that they offer in this arena. We suggest that the ease of viewing and manipulating molecular structures and dynamics, and the ability to modify structures on the fly (e.g., adding or deleting atoms) makes modern interactive VR a valuable tool to add to the armoury of drug development methods.Comment: 19 pages, 3 figure

Simulating and optimizing electrical current flow and neuronal activation in retinal implants

© 2018 Dr Timothy Bede Esler[Abstract Withheld

A Computational Model for Epidural Electrical Stimulation of Spinal Sensorimotor Circuits

Epidural electrical stimulation (EES) of lumbosacral segments can restore a range of movements after spinal cord injury. However, the mechanisms and neural structures through which EES facilitates movement execution remain unclear. Here, we designed a computational model and performed in vivo experiments to investigate the type of fibers, neurons, and circuits recruited in response to EES. We first developed a realistic finite element computer model of rat lumbosacral segments to identify the currents generated by EES. To evaluate the impact of these currents on sensorimotor circuits, we coupled this model with an anatomically realistic axon-cable model of motoneurons, interneurons, and myelinated afferent fibers for antagonistic ankle muscles. Comparisons between computer simulations and experiments revealed the ability of the model to predict EES-evoked motor responses over multiple intensities and locations. Analysis of the recruited neural structures revealed the lack of direct influence of EES on motoneurons and interneurons. Simulations and pharmacological experiments demonstrated that EES engages spinal circuits trans-synaptically through the recruitment of myelinated afferent fibers. The model also predicted the capacity of spatially distinct EES to modulate side-specific limb movements and, to a lesser extent, extension versus flexion. These predictions were confirmed during standing and walking enabled by EES in spinal rats. These combined results provide a mechanistic framework for the design of spinal neuroprosthetic systems to improve standing and walking after neurological disorders