The surgical community has long reported the need for improved control of surgical graspers when handling delicate soft tissues, both to avoid the over application of force which leads to trauma, and to avoid tissue slip. The majority of research has sought to mitigate these issues through the integration of force feedback into the graspers. In this work we investigate an alternative strategy in which the grasper design is engineered to create preferential localised slip, also known as incipient slip, on the premise that this can be detected before the onset of macro slip, allowing graspers to use the minimum force required to maintain stable control. We demonstrate the ability to encourage incipient slip in a predictable and repeatable manner through the design of the grasper face profile and pattern. This provides an important foundation for development of sensing systems capable of detecting these slips during surgery to improve operative outcomes.
Despite recent advances in modern surgical robotic systems, an ongoing challenge remains their limited ability to control grasp force. This can impair surgical performance as a result of either tissue slippage or trauma from excessive grasp force. In this work we investigate a force control strategy to address this challenge based on the detection of incipient slip. Our approach employs a grasper face whose shape is engineered to encourage preferential localised slips that can be sensed using embedded displacement sensors prior to gross slip occurring. This novel approach enables closed loop control of the grasping force to prevent gross slip whilst applying minimal force. In this paper we first demonstrate the efficacy of sensing incipient slip and then demonstrate how this can form a robust closed loop grasping system to maintain stable control of tissue. Results demonstrate that this approach can achieve equivalent grasping performance to a scheme employing a fixed maximal grasping force while reducing tissue loading, and thus risk of trauma. This provides the foundation for the development of automated surgical robots with adaptive grasp force control.
Background: The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has placed a significant demand on healthcare providers (HCPs) to provide respiratory support for patients with moderate to severe symptoms. Continuous Positive Airway Pressure (CPAP) non-invasive ventilation can help patients with moderate symptoms to avoid the need for invasive ventilation in intensive care. However, existing CPAP systems can be complex (and thus expensive) or require high levels of oxygen, limiting their use in resource-stretched environments.Technical Development + Testing: The LeVe (“Light”) CPAP system was developed using principles of frugal innovation to produce a solution of low complexity and high resource efficiency. The LeVe system exploits the air flow dynamics of electric fan blowers which are inherently suited to delivery of positive pressure at appropriate flow rates for CPAP. Laboratory evaluation demonstrated that performance of the LeVe system was equivalent to other commercially available systems used to deliver CPAP, achieving a 10 cm H2O target pressure within 2.4% RMS error and 50–70% FiO2 dependent with 10 L/min oxygen from a commercial concentrator.Pilot Evaluation: The LeVe CPAP system was tested to evaluate safety and acceptability in a group of ten healthy volunteers at Mengo Hospital in Kampala, Uganda. The study demonstrated that the system can be used safely without inducing hypoxia or hypercapnia and that its use was well-tolerated by users, with no adverse events reported.Conclusions: To provide respiratory support for the high patient numbers associated with the COVID-19 pandemic, healthcare providers require resource efficient solutions. We have shown that this can be achieved through frugal engineering of a CPAP ventilation system, in a system which is safe for use and well-tolerated in healthy volunteers. This approach may also benefit other respiratory conditions which often go unaddressed in Low and Middle Income Countries (LMICs) for want of context-appropriate technology designed for the limited oxygen resources available.
The limited grasping control available in Robot Assisted Surgery is considered a significant limitation of the technology. Traditionally the integration of haptic feedback has been proposed to resolve this issue but has found limited adoption. Here we investigate an alternate approach based on the concept of detecting localised slips caused by the intrinsic elastic properties of soft tissues. This method allows for the early detection of slip so that mitigating actions can be taken before gross slip can occur, allowing the grasper to minimise the force required to maintain stable grasp control. In this paper we detail the design of a sensor developed to detect incipient slip by monitoring the relative difference in tissue movement at the front and back of the grasper, caused by tissue slip. We then demonstrate the sensor's efficacy for the early detection of slip, as well as its ability to automate grasping under representative surgical conditions, with the automated case providing comparable performance to one which uses the maximum allowable grasp force. This work provides evidence that the slip detection methodology developed is consistently able to detect incipient slip before macro slip occurs, thus offering a strong basis for its use in automating surgical grasping tasks to avoid tissue trauma and slip.
The COVID-19 pandemic has placed a dramatic increase in demand on healthcare providers to provide respiratory support for patients with moderate to severe symptoms. In conjunction, the pandemic has challenged existing supply-chains to meet demands for medical equipment and resources. In response to these challenges, we report our work to repurpose two existing non-invasive ventilation (NIV) systems to provide solutions for the delivery of oxygen-enriched CPAP ventilation which are inherently resource and oxygen-efficient. We consider adaptation of CPAP systems typically used for sleep apnoea, together with a new Venturi-valve design which can be readily produced through 3D printing. Our aim in both cases was to support Positive end-expiratory pressure (PEEP) of ≥10cmH2O while achieving ≥40% FiO2. This supports a crucial part in the patient pathway for COVID-19 treatment, helping to provide early respiratory support prior to invasive ventilation options in the ICU.
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