Micro-robotic Cell Injection Training in a CAVE

This paper focuses on the design of an evaluation made to a large-scale virtual reality micro-robotic cell injection training system. The aim of the evaluation is to empirically investigate the usability and effectiveness of three distinct display configurations and the input controller employed in the system. The data was gathered through a set of experiments with human participants. Participants’ performance against metrics such as success rate and magnitude of error was considered in the evaluation. For the experiments, participants were randomly divided into six equal sized groups where each group was provided with a specific combination of display configuration and haptic guidance mode. The participants performed ten injections and the time and position of the virtual micropipette tip were recorded. Data was analysed using descriptive statistics and performance comparison between groups was conducted. Additionally three groups also underwent two subsequent sessions, training and post-training, as a basis to evaluate the effectiveness of the training with haptic guidance by comparing participants’ performance before and after the training session. The implementation of the designed evaluation has contributed to the conclusions drawn which suggest the proposed large-scale virtual reality system as a feasible training tool for micro-robotic cell injection procedure, and recommendations for future work are proposed

Haptic feedback in teleoperation in Micro-and Nano-Worlds.

International audienceRobotic systems have been developed to handle very small objects, but their use remains complex and necessitates long-duration training. Simulators, such as molecular simulators, can provide access to large amounts of raw data, but only highly trained users can interpret the results of such systems. Haptic feedback in teleoperation, which provides force-feedback to an operator, appears to be a promising solution for interaction with such systems, as it allows intuitiveness and flexibility. However several issues arise while implementing teleoperation schemes at the micro-nanoscale, owing to complex force-fields that must be transmitted to users, and scaling differences between the haptic device and the manipulated objects. Major advances in such technology have been made in recent years. This chapter reviews the main systems in this area and highlights how some fundamental issues in teleoperation for micro- and nano-scale applications have been addressed. The chapter considers three types of teleoperation, including: (1) direct (manipulation of real objects); (2) virtual (use of simulators); and (3) augmented (combining real robotic systems and simulators). Remaining issues that must be addressed for further advances in teleoperation for micro-nanoworlds are also discussed, including: (1) comprehension of phenomena that dictate very small object (< 500 micrometers) behavior; and (2) design of intuitive 3-D manipulation systems. Design guidelines to realize an intuitive haptic feedback teleoperation system at the micro-nanoscale level are proposed

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

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

Remote Access and Computerized User Control of Robotic Micromanipulators

Nano- and micromanipulators are critical research tools in numerous fields including micro-manufacturing and disease study. Despite their importance, nano- and micromanipulation systems remain inaccessible to many groups due to price and lack of portability. An intuitive and remotely accessible manipulation system helps mitigate this access problem. Previously, optimal control hardware for single-probe manipulation and the effect of latency on user performance were not well understood. Remote access demands full computerization; graphical user interfaces with networking capabilities were developed to fulfill this requirement and allow the use of numerous hardware controllers. Virtual environments were created to simulate the use of a manipulator with full parametric control and measurement capabilities. Users completed simulated tasks with each device and were surveyed about their perceptions. User performance with a commercial manipulator controller was exceeded by performance with both a computer mouse and pen tablet. Latency was imposed within the virtual environment to study it’s effects and establish guidelines as to which latency ranges are acceptable for long-range remote manipulation. User performance began to degrade noticeably at 100 ms and severely at 400 ms and performance with the mouse degraded the least as latency increased. A computer vision system for analyzing carbon nanotube arrays was developed so the computation time could be compared to acceptable system latency. The system characterizes the arrays to a high degree of accuracy and most of the measurement types of obtainable fast enough for real-time analysis

Bioengineering, augmented reality, and robotic surgery in vascular surgery: A literature review

Biomedical engineering integrates a variety of applied sciences with life sciences to improve human health and reduce the invasiveness of surgical procedures. Technological advances, achieved through biomedical engineering, have contributed to significant improvements in the field of vascular and endovascular surgery. This paper aims to review the most cutting-edge technologies of the last decade involving the use of augmented reality devices and robotic systems in vascular surgery, highlighting benefits and limitations. Accordingly, two distinct literature surveys were conducted through the PubMed database: the first review provides a comprehensive assessment of augmented reality technologies, including the different techniques available for the visualization of virtual content (11 papers revised); the second review collects studies with bioengineering content that highlight the research trend in robotic vascular surgery, excluding works focused only on the clinical use of commercially available robotic systems (15 papers revised). Technological flow is constant and further advances in imaging techniques and hardware components will inevitably bring new tools for a clinical translation of innovative therapeutic strategies in vascular surgery

Robotic Navigation Autonomy for Subretinal Injection via Intelligent Real-Time Virtual iOCT Volume Slicing

In the last decade, various robotic platforms have been introduced that could support delicate retinal surgeries. Concurrently, to provide semantic understanding of the surgical area, recent advances have enabled microscope-integrated intraoperative Optical Coherent Tomography (iOCT) with high-resolution 3D imaging at near video rate. The combination of robotics and semantic understanding enables task autonomy in robotic retinal surgery, such as for subretinal injection. This procedure requires precise needle insertion for best treatment outcomes. However, merging robotic systems with iOCT introduces new challenges. These include, but are not limited to high demands on data processing rates and dynamic registration of these systems during the procedure. In this work, we propose a framework for autonomous robotic navigation for subretinal injection, based on intelligent real-time processing of iOCT volumes. Our method consists of an instrument pose estimation method, an online registration between the robotic and the iOCT system, and trajectory planning tailored for navigation to an injection target. We also introduce intelligent virtual B-scans, a volume slicing approach for rapid instrument pose estimation, which is enabled by Convolutional Neural Networks (CNNs). Our experiments on ex-vivo porcine eyes demonstrate the precision and repeatability of the method. Finally, we discuss identified challenges in this work and suggest potential solutions to further the development of such systems