SummarySyringe infusion pumps are used for the administration of short‐acting drugs in anaesthesia and critical care medicine, but are prone to flow irregularities at low flow rates. A flow‐controlled syringe infusion pump using an integrated flow sensor for feedback control represents a new approach to overcoming these limitations. This study compares the performance of a prototype flow‐controlled syringe pump both at start‐up, and during vertical displacement manoeuvres, with that of a standard infusion syringe pump. The novel pump almost completely eliminated delays at start‐up and flow irregularities during hydrostatic pressure changes. Related fluctuations in plasma drug concentration were minimised and the known disadvantages of standard syringe infusion pumps currently used in clinical practice were reduced. Besides providing fast start‐up to steady‐state flow and precise continuous drug delivery at low flow rates during hydrostatic pressure changes, the new pump offers the potential for the development of target‐controlled infusion algorithms for short‐acting cardiovascular and other drugs.
Ventricular assist devices (VADs) are an established treatment option for heart failure (HF). However, the devices are often plagued by material‐related hemocompatibility issues. In contrast to continuous flow VADs with high shear stresses, pulsatile VADs (pVADs) offer the potential for an endothelial cell coating that promises to prevent many adverse events caused by an insufficient hemocompatibility. However, their size and weight often precludes their intracorporeal implantation. A reduction of the pump body size and weight of the pump could be achieved by an increase in the stroke frequency while maintaining a similar cardiac output. We present a new pVAD system consisting of a pump and an actuator specifically designed for actuation frequencies of up to 240 bpm. In vitro and in vivo results of the short‐term reaction of the cardiovascular system show no significant changes in left ventricular and aortic pressure between actuation frequencies from 60 to 240 bpm. The aortic pulsatility increases when the actuation frequency is raised while the heart rate remains unaffected in vivo. These results lead us to the conclusion that the cardiovascular system tolerates short‐term increases of the pVAD stroke frequencies.
The user's gaze can provide important information for human–machine interaction, but the analysis of manual gaze data is extremely time-consuming, inhibiting wide adoption in usability studies. Existing methods for automated areas of interest (AOI) analysis cannot be applied to tangible products with a screen-based user interface (UI), which have become ubiquitous in everyday life. The objective of this paper is to present and evaluate a method to automatically map the user's gaze to dynamic AOIs on tangible screen-based UIs based on computer vision and deep learning. This paper presents an algorithm for automated Dynamic AOI Mapping (aDAM), which allows the automated mapping of gaze data recorded with mobile eye tracking to the predefined AOIs on tangible screen-based UIs. The evaluation of the algorithm is performed using two medical devices, which represent two extreme examples of tangible screen-based UIs. The different elements of aDAM are examined for accuracy and robustness, as well as the time saved compared to manual mapping. The break-even point for an analyst's effort for aDAM compared to manual analysis is found to be 8.9 min gaze data time. The accuracy and robustness of both the automated gaze mapping and the screen matching indicate that aDAM can be applied to a wide range of products. aDAM allows, for the first time, automated AOI analysis of tangible screen-based UIs with AOIs that dynamically change over time. The algorithm requires some additional initial input for the setup and training, but analyzed gaze data duration and effort is only determined by computation time and does not require any additional manual work thereafter. The efficiency of the approach has the potential for a broader adoption of mobile eye tracking in usability testing for the development of new products and may contribute to a more data-driven usability engineering process in the future.
Modelling of mechatronic systems often results in implicit model description. Simulation systems provide different strategies to deal with this kind of problem, resulting in different modelling approaches. For this purpose, Mathwork's MATLAB system offers in its basic MATLAB system at programming level implicit ODE solvers, and in its toolboxes Simulink and SimMechanics (on basis of the Modelica-like system SimScape) graphical modelling environment. This Benchmark Study compares these modelling approaches and the simulation efficiency and results on basis of the ARGESIM Benchmark C11 'SCARA Robot'. Additionally, the contribution's investigations present a tuning of the PID control for point-to-point movement with and without collision prevention and introduce a trajectory tracking control with collision prevention, which improves the performance essentially.
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