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Model-Based Dependability Analysis of Programmable Drug Infusion Pumps

机译:基于模型的可编程输液泵的可靠性分析

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Infusion pumps are commonly used in home/hospital care to inject drugs into a patient at programmable rates over time. However, in practice, a combination of faults including software errors, mechanical failures and human error can lead to catastrophic situations, causing death or serious harm to the patient. Dependability analysis techniques such as failure mode effect analysis (FMEA) can be used to predict the worst case outcomes of such faults and facilitate the development of remedies against them. In this paper, we present the use of model-checking to automate the dependability analysis of programmable, real-time medical devices. Our approach uses timed and hybrid automata to model the real-time operation of the medical device and its interactions with the care giver and the patient. Common failure modes arising from device failures and human error are modeled in our framework. Specifically, we use "mistake models" derived from human factor studies to model the effects of mistakes committed by the operator. We present a case-study involving an infusion pump used to manage pain through the infusion of analgesic drugs. The dynamics of analgesic drugs are modeled by empirically validated pharmacokinetic models. Using model checking, our technique can systematically explore numerous combinations of failures and characterize the worse case effects of these failures.
机译:输液泵通常用于家庭/医院护理中,以便随时间推移以可编程的速率将药物注入患者体内。但是,在实践中,包括软件错误,机械故障和人为错误在内的各种故障组合可能导致灾难性情况,从而导致死亡或严重伤害患者。诸如故障模式影响分析(FMEA)之类的可靠性分析技术可用于预测此类故障的最坏情况结果并促进针对这些故障的补救措施的开发。在本文中,我们介绍了使用模型检查来自动化可编程实时医疗设备的可靠性分析。我们的方法使用定时和混合自动机对医疗设备的实时操作及其与护理人员和患者的交互进行建模。由设备故障和人为错误引起的常见故障模式在我们的框架中建模。具体来说,我们使用源自人为因素研究的“错误模型”来对操作员犯下的错误的影响进行建模。我们提供了一个案例研究,涉及一个输液泵,用于通过输注止痛药来控制疼痛。通过经验验证的药代动力学模型来模拟镇痛药的动力学。使用模型检查,我们的技术可以系统地探索故障的多种组合,并表征这些故障的最坏情况。

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