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Medical warning system based on Internet of Things using fog computing

机译:基于使用雾计算的东西的医疗警告系统

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Remote patient monitoring is essential for many patients that are suffering from acute diseases such as different heart conditions. Continuous health monitoring can provide medical services that consider the current medical state of the patient and to predict or early-detect future potentially critical situations. In this regard, Internet of Things as a multidisciplinary paradigm can provide profound impacts. However, the current IoT-based systems may encounter difficulties to provide continuous and real time patient monitoring due to issues in data analytics. In this paper, we introduce a new IoT-based approach to offer smart medical warning in personalized patient monitoring. The proposed approach consider local computing paradigm enabled by machine learning algorithms and automate management of system components in computing section. The proposed system is evaluated via a case study concerning continuous patient monitoring to early-detect patient deterioration via arrhythmia in ECG signal.
机译:远程患者监测对于许多患有急性疾病如不同心脏病的患者至关重要。持续健康监测可以提供考虑当前患者的医疗状态和预测或早期检测未来潜在危急情况的医疗服务。在这方面,作为多学科范例的东西互联网可以提供深刻的影响。然而,由于数据分析中的问题,当前基于物联网的系统可能遇到难以提供连续和实时患者监测的困难。在本文中,我们介绍了一种新的基于物联网的方法,以便在个性化患者监测中提供智能医疗警告。所提出的方法考虑通过机器学习算法启用的本地计算范例,并在计算部分中自动化系统组件的管理。所提出的系统通过案例研究进行了关于通过ECG信号中的心律失常的早期患者监测的连续患者监测。

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