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Intelligent Control System applied to In Vitro Ventricular Assist Device Test Bench for Decision Support

机译:智能控制系统适用于体外心室辅助装置测试台进行决策支持

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The Ventricular Assist Device (VAD) is a mechatronic device used as a therapy for advanced heart failure (HF) in patients who are candidates for organ transplantation. Although the most frequent application is still a short-term (transplant bridge) therapy strategy, long-term use (destination therapy) has been increasing because of the increased longevity of the population using these devices. However, according to the INTERMACS report, adverse events are observed that compromise the survival rate of implanted patients, among which we have the malfunction of the VAD. The occurrence of this event influences the reliability and availability of the device. In this way, the development of resources and techniques to improve the robustness, availability and reliability of these devices is indispansable for the medical equipment industry. This prospective work proposes an in vitro test bench with intelligent behavior, which allows to put of VAD in operation. The test bench has rotation, vibration, energy, temperature, pressure and flow sensors that are monitored by a computer system. In order to identify malfunctions, standard curves have been developed for the variables being monitored. When a deviation of a variable with respect to its standard curve appears, a fault is characterized. The collection, treatment and monitoring of this failure data is accomplished by the use of Big Data Analytics technology. The method proposed in this work allows the verification and validation of a VAD, based on the behavioral data collected during the tests, through the appropriate protocols and the in vitro procedures.
机译:心室辅助装置(VAD)是一种机制装置,用作用于器官移植候选者的患者的晚期心力衰竭(HF)的治疗。虽然最常见的应用仍然是短期(移植桥)治疗策略,但长期使用(目的地治疗)由于使用这些设备的寿命增加了寿命而增加。然而,根据Intermacs报告,观察到不良事件,损害植入患者的存活率,其中我们有VAD的故障。此事件的发生影响设备的可靠性和可用性。通过这种方式,可以开发资源和技术,以提高这些设备的稳健性,可用性和可靠性对于医疗设备行业是不可起来的。该潜在工作提出了一种具有智能行为的体外测试台,可以在运行中放入VAD。测试台具有由计算机系统监控的旋转,振动,能量,温度,压力和流量传感器。为了识别出故障,已经为正在监控的变量开发的标准曲线。当出现相对于其标准曲线的变量偏差时,表征了一个故障。通过使用大数据分析技术来实现对此故障数据的收集,处理和监控。本作品中提出的方法允许根据在测试期间收集的行为数据,通过适当的协议和体外程序来验证和验证VAD。

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