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

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

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

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

Modeling and experimental validation of a parallel microrobot for biomanipulation

The main purpose of this project is the development of a commercial micropositioner's (SmarPod 115.25, SmarAct GmbH) geometrical model. SmarPod is characterized by parallel kinematics and is employed for precise and accurate sample's positioning under SEM microscope, being vacuum-compatible, for various applications. Geometrical modeling represents the preliminar step to fully understand, and possibly improve, robot's closed loop behaviour in terms of task's quality precision, when enterprises does not provide sufficient documentation. The robotic system, in fact, represents in this case a "black box" from which it's possible to extract information. This step is essential in order to improve, consequently, the reliability of bio-microsystem manipulation and characterization. Disposing of a detailed microrobot's model becomes essential to deal with the typical lack of sensing at microscale, as it allows a 3D precise and adequate reconstruction, realized through proper softwares, of the manipulation set-up. The roles of Virtual Reality (VR) and of simulations, carried out, in this case, in Blender environment, are asserted as well as an essential helping tool in mycrosystem's task planning. Blender is a professional free and open-source 3D computer graphics software and it is proven to be a basic instrument to validate microrobot's model, even to simplify it in case of complex system's geometries

Factors of Micromanipulation Accuracy and Learning

Micromanipulation refers to the manipulation under a microscope in order to perform delicate procedures. It is difficult for humans to manipulate objects accurately under a microscope due to tremor and imperfect perception, limiting performance. This project seeks to understand factors affecting accuracy in micromanipulation, and to propose strategies for learning improving accuracy. Psychomotor experiments were conducted using computer-controlled setups to determine how various feedback modalities and learning methods can influence micromanipulation performance. In a first experiment, static and motion accuracy of surgeons, medical students and non-medical students under different magniification levels and grip force settings were compared. A second experiment investigated whether the non-dominant hand placed close to the target can contribute to accurate pointing of the dominant hand. A third experiment tested a training strategy for micromanipulation using unstable dynamics to magnify motion error, a strategy shown to be decreasing deviation in large arm movements. Two virtual reality (VR) modules were then developed to train needle grasping and needle insertion tasks, two primitive tasks in a microsurgery suturing procedure. The modules provided the trainee with a visual display in stereoscopic view and information on their grip, tool position and angles. Using the VR module, a study examining effects of visual cues was conducted to train tool orientation. Results from these studies suggested that it is possible to learn and improve accuracy in micromanipulation using appropriate sensorimotor feedback and training

Virtual Reality Based Environment for Orthopedic Surgery (Veos)

The traditional way of teaching surgery involves students observing a �live� surgery and then gradually assisting experienced surgeons. The creation of a Virtual Reality environment for orthopedic surgery (VEOS) can be beneficial in improving the quality of training while decreasing the time needed for training. Developing such virtual environments for educational and training purposes can supplement existing approaches. In this research, the design and development of a virtual reality based environment for orthopedic surgery is described. The scope of the simulation environment is restricted to an orthopedic surgery process known as Less Invasive Stabilization System (LISS) surgery. The primary knowledge source for the LISS surgical process was Miguel A. Pirela-Cruz (Head of Orthopedic Surgery and Rehabilitation, Texas Tech University Health Sciences Center (TTHSC)). The VEOS was designed and developed on a PC based platform. The developed VEOS was validated through interactions with surgical residents at TTHSC. Feedback from residents and our collaborator Miguel A. Pirela-Cruz was used to make necessary modifications to the surgical environment.Industrial Engineering & Managemen

Technology 2003: The Fourth National Technology Transfer Conference and Exposition, volume 2

Proceedings from symposia of the Technology 2003 Conference and Exposition, Dec. 7-9, 1993, Anaheim, CA, are presented. Volume 2 features papers on artificial intelligence, CAD&E, computer hardware, computer software, information management, photonics, robotics, test and measurement, video and imaging, and virtual reality/simulation

Scalability study for robotic hand platform

The goal of this thesis project was to determine the lower limit of scale for the RIT robotic grasping hand. This was accomplished using a combination of computer simulation and experimental studies. A force analysis was conducted to determine the size of air muscles required to achieve appropriate contact forces at a smaller scale. Input variables, such as the actuation force and tendon return force, were determined experimentally. A dynamic computer model of the hand system was then created using Recurdyn. This was used to predict the contact (grasping) force of the fingers at full-scale, half-scale, and quarter-scale. Correlation between the computer model and physical testing was achieved for both a life-size and half-scale finger assembly. To further demonstrate the scalability of the hand design, both half and quarter-scale robotic hand rapid prototype assemblies were built using 3D printing techniques. This thesis work identified the point where further miniaturization would require a change in the manufacturing process to micro-fabrication. Several techniques were compared as potential methods for making a production intent quarter-scale robotic hand. Investment casting, Swiss machining, and Selective Laser Sintering were the manufacturing techniques considered. A quarter-scale robotic hand tested the limits of each technology. Below this scale, micro-machining would be required. The break point for the current actuation method, air muscles, was also explored. Below the quarter-scale, an alternative actuation method would also be required. Electroactive Polymers were discussed as an option for the micro-scale. In summary, a dynamic model of the RIT robotic grasping hand was created and validated as scalable at full and half-scales. The model was then used to predict finger contact forces at the quarter-scale. The quarter-scale was identified as the break point in terms of the current RIT robotic grasping hand based on both manufacturing and actuation. A novel, prototype quarter-scale robotic hand assembly was successfully built by an additive manufacturing process, a high resolution 3D printer. However, further miniaturization would require alternate manufacturing techniques and actuation mechanisms