Strain Sensor-Embedded Soft Pneumatic Actuators for Extension and Bending Feedback

For soft robots to leave the lab and enter unstructured environments, proprioception is required to understand how interactions in the field affect the soft structure. In this work, we present sensor-embedded soft pneumatic actuators (sSPA) that can observe both extension and bending. The sensors are strain sensitive capacitors, which are bonded to the interior of fiber-reinforced extension actuators on opposing faces. This construction allows extension and bending to be measured by calculating the mean and difference in sensor responses, respectively. The sSPAs are bonded together to form a flat fascicle to increase the force output and prevent buckling under load, and are robust to component failure by incorporating redundancy. In this paper, we discuss the fabrication of the sensors and their subsequent integration into the actuators. We also report the work capacity and sensor. response of the sSPA fascicles under extension, bending, and the combination of both modes of deformation. The sensor- embedded soft pneumatic actuators presented here will advance the field of soft robotics by enabling closed-loop control of soft robots

An Any-Resolution Distributed Pressure Localization Scheme Using a Capacitive Soft Sensor Skin

We present a method to determine the location of an applied pressure on a large area, monolithic silicone based capacitive sensor. In contrast to pressure sensor arrays composed of n x n discrete sensors, we utilize a single sensor body with a single instrumentation interface to detect n pixels. We interrogate the capacitive sensor at different frequencies, thus modulating the effective length of the sensor. These interrogation frequencies are governed by the sensor’s total capacitance, resistance, and desired spatial resolution of the sensor. We developed an analytical model to calculate the frequency response at different length segments of the sensor and used the results to determine the interrogation frequencies for experimental studies. We performed experimental tests on a 1 x n sensor strip and an n x n sensor sheet and showed that we could attain greater than 90% accuracy in predicting the location of the applied pressure using a model generated by a multi-class kernel support vector machine. This approach towards distributed localization of point pressures greatly reduces the hardware complexity in comparison to discrete sensor arrays and increases the physical robustness of the system

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries