Multipoint haptic guidance for micrograsping systems

The ability to perform accurate micromanipulation offers wide-reaching benefits and is of increasing interest to researchers. Recent research into microgripper, microtweezer, and microforcep systems contributes toward accurate micrograsping and manipulation. Despite these efforts, achieving adequate operator control remains a distinct research challenge. Haptic interfaces interact with the human's haptic modality and offer the ability to enhance the operator's controllability of micromanipulation systems. Our previous work introduced single-point haptic guidance to assist the operator during intracellular microinjection. This paper extends the approach to propose multipoint haptic guidance for micrograsping tasks. Accurate micrograsping is valuable in many applications, including microassembly and biomanipulation. A multipoint haptic gripper facilitates haptic interaction, and haptic guidance assists the operator in controlling systems suitable for micrograsping. Force fields are used to guide the operator to suitable grasp points on micrometer-sized objects and consist of attractive and repulsive forces. The ability of the force field to effectively assist the operator in grasping the cell is evaluated using a virtual environment. Evaluation results demonstrate the ability of the approach to significantly reduce participants' average grasping error.

Haptic virtual reality training environment for micro-robotic cell injection

Micro-robotic cell injection is typically performed manually by a trainedbio-operator, and success rates are often low. To enhance bio-operator performance during real-time cell injection, our earlier work introduced a haptically-enabled micro-robotic cell injection system. The system employed haptic virtual fixtures to provide haptic guidance according to articular performance metrics. This paper extends the work by replicating the system within a virtual reality (VR) environment for bio-operator training. Using the virtual environment, the bio-operator is able to control the virtual injection process in the same way they would with the physical haptic micro-robotic cell injection system, while benefiting from the enhanced visualisation capabilities offered by the 3D VR environment. The system is achieved using cost-effective components offering training at much lower cost than using the physical system.

Youth Depression Alleviation-Augmentation with an anti-inflammatory agent (YoDA-A): protocol and rationale for a placebo-controlled randomized trial of rosuvastatin and aspirin

AIM: There is growing support for the role of inflammation and oxidative stress in the pathophysiology of major depressive disorder (MDD). This has led to the development of novel strategies targeting inflammation in the treatment of depression. Rosuvastatin and aspirin have well-documented, anti-inflammatory and antioxidant properties. The aim of the Youth Depression Alleviation: Augmentation with an anti-inflammatory agent (YoDA-A) study is to determine whether individuals receiving adjunctive anti-inflammatory agents, aspirin and rosuvastatin experience a reduction in the severity of MDD compared with individuals receiving placebo. METHODS: YoDA-A is a 12-week triple-blind, randomized controlled trial funded by the National Health and Medical Research Council, Australia. Participants aged 15-25, with moderate-to-severe MDD, are allocated to receive either 10 mg/day rosuvastatin, 100 mg/day aspirin, or placebo, in addition to treatment as usual. Participants are assessed at baseline and at weeks 4, 8, 12 and 26. The primary outcome is change in the Montgomery-Åsberg Depression Rating Scale (MADRS) from baseline to week 12. RESULTS: The study is planned to be completed in 2017. At date of publication, 85 participants have been recruited. CONCLUSION: Timely and targeted intervention for youth MDD is crucial. Given the paucity of new agents to treat youth MDD, adjunctive trials are not only pragmatic and 'real-world', but additionally aim to target shortfalls in conventional medications. This study has the potential to first provide two new adjunctive treatment options for youth MDD; aspirin and rosuvastatin. Second, this study will serve as proof of principle of the role of inflammation in MDD.

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.

Applying inverse just-noticeable-differences of velocity to position data for haptic data reduction

ust-Noticeable-Differences (JND) as a dead-band in perceptual analysis has been widely used for more than a decade. This technique has been employed for data reduction in hap tic data transmission systems by several researchers. In fact, researchers use two different JND coefficients that are JNDV and JNDF for velocity and force data respectively. For position data, they usually rely on the resolution of hap tic display device to omit data that are unperceivable to human. In this paper, pruning undesirable position data that are produced by the vibration of the device or subject and/or noise in transmission line is addressed. It is shown that using inverse JNDV for position data can prune undesirable position data. Comparison of the results of the proposed method in this paper with several well known filters and some available methods proposed by other researchers is performed. It is shown that combination of JNDV could provide lower error with desirable curve smoothness, and as little as possible computation effort and complexity. It also has been shown that this method reduces much more data rather than using forward-JNDV.

Countering Improvised explosive devices through a multi-point haptic teleoperation system

Improvised Explosive Devices (IEDs) are reported as the number one cause of injury and death for allied troops in the current theater of operation. Current stand-off technologies for Counter IED (CIED) tasks rely on robotic platforms that have not improved in capability over the past decade to combat the ever increasing threat of IEDs. While they provide operational capability, the effectiveness of these platforms is limited. This is because they primarily utilise video and audio feedback, and require extensive training and specialist operators. Recent operational experience has demonstrated the need for robotic systems that are highly capable, yet easily operable for high fidelity manipulation. Force feedback provides an operator with more intuitive control of a robotic system. This sense of touch allows an operator to obtain a sense of feel from a stand-off location of what the robot touches or grasps through a human-robot interface. This paper reports the design and development of a Haptically-Enabled Counter IED robotic system that was funded by the Australian Defence Force. The presented work focuses on the design methodology for the system, and provides the results of the manipulator analysis and trial outcomes.

Force reflection distribution of haptic devices

Haptically enabled virtual reality systems facilitate rapid and low cost testing for process design, training practices and ergonomic analysis in many manufacturing industries, particularly automotive and aerospace. In this work we design a validation framework to validate the dynamic forces displayed by haptic display devices using a robot arm equipped with a force sensor. The validation framework is completely autonomous to ensure unbiased characterization. Measured force magnitude and the direction of the sensed force vector are the main criteria used in this work.