Majma Negar, Babamir Seyed Morteza, Monadjemi Amirhassan
Department of Computer, University of Kashan, Kashan, Iran.
Naghshejahan Higher Education Institute, Isfahan, Iran.
J Med Syst. 2017 Feb;41(2):27. doi: 10.1007/s10916-016-0664-5. Epub 2016 Dec 22.
Today, implanted medical devices are increasingly used for many patients and in case of diverse health problems. However, several runtime problems and errors are reported by the relevant organizations, even resulting in patient death. One of those devices is the pacemaker. The pacemaker is a device helping the patient to regulate the heartbeat by connecting to the cardiac vessels. This device is directed by its software, so any failure in this software causes a serious malfunction. Therefore, this study aims to a better way to monitor the device's software behavior to decrease the failure risk. Accordingly, we supervise the runtime function and status of the software. The software verification means examining limitations and needs of the system users by the system running software. In this paper, a method to verify the pacemaker software, based on the fuzzy function of the device, is presented. So, the function limitations of the device are identified and presented as fuzzy rules and then the device is verified based on the hierarchical Fuzzy Colored Petri-net (FCPN), which is formed considering the software limits. Regarding the experiences of using: 1) Fuzzy Petri-nets (FPN) to verify insulin pumps, 2) Colored Petri-nets (CPN) to verify the pacemaker and 3) To verify the pacemaker by a software agent with Petri-network based knowledge, which we gained during the previous studies, the runtime behavior of the pacemaker software is examined by HFCPN, in this paper. This is considered a developing step compared to the earlier work. HFCPN in this paper, compared to the FPN and CPN used in our previous studies reduces the complexity. By presenting the Petri-net (PN) in a hierarchical form, the verification runtime, decreased as 90.61% compared to the verification runtime in the earlier work. Since we need an inference engine in the runtime verification, we used the HFCPN to enhance the performance of the inference engine.
如今，植入式医疗设备越来越多地被用于许多患者以及各种健康问题的治疗中。然而，相关组织报告了一些运行时问题和错误，甚至导致患者死亡。其中一种设备就是心脏起搏器。心脏起搏器是一种通过连接心脏血管来帮助患者调节心跳的设备。该设备由其软件控制，因此该软件的任何故障都会导致严重的功能故障。因此，本研究旨在找到一种更好的方法来监控设备软件行为，以降低故障风险。相应地，我们对软件的运行时功能和状态进行监督。软件验证是指通过运行软件的系统来检查系统用户的限制和需求。本文提出了一种基于设备模糊功能来验证心脏起搏器软件的方法。因此，识别出设备的功能限制并将其表示为模糊规则，然后基于考虑软件限制而形成的分层模糊着色Petri网（FCPN）对设备进行验证。关于使用经验：1）使用模糊Petri网（FPN）验证胰岛素泵，2）使用着色Petri网（CPN）验证心脏起搏器，以及3）在前一项研究中我们通过基于Petri网知识的软件代理验证心脏起搏器，本文通过HFCPN检查心脏起搏器软件的运行时行为。与早期工作相比，这被认为是一个发展步骤。本文中的HFCPN与我们之前研究中使用的FPN和CPN相比，降低了复杂性。通过以分层形式呈现Petri网（PN），验证运行时与早期工作中的验证运行时相比减少了90.61%。由于我们在运行时验证中需要一个推理引擎，我们使用HFCPN来提高推理引擎的性能。
