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A semantic-enabled and context-aware monitoring system for the internet of medical things

机译：用于医学互联网的语义启用和上下文感知监控系统

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The emergence of the Internet of Things (IoT) in the medical field has led to the massive deployment of a myriad of medical connected objects (MCOs). These MCOs are being developed and implemented for remote healthcare monitoring purposes including elderly patients with chronic diseases, pregnant women, and patients with disabilities. Accordingly, different associated challenges are emerging and include the heterogeneity of the gathered health data from these MCOs with ever-changing contexts. These contexts are relative to the continuous change of constraints and requirements of the MCOs deployment (time, location, state). Other contexts are related to the patient (medical record, state, age, sex, etc.) that should be taken into account to ensure a more precise and appropriate treatment of the patient. These challenges are difficult to address due to the absence of a reference model for describing the health data and their sources and linking these data with their contexts. This article addresses this problem and introduces a semantic-based context-aware system (IoT Medicare system) for patient monitoring with MCOs. This system is based on a core domain ontology (HealthIoT-O), that is, designed to describe the semantic of heterogeneous MCOs and their data. Moreover, an efficient interpretation and management of this knowledge in diverse contexts are ensured through SWRL rules such as the verification of the proper functioning of the MCOs and the analysis of the health data for diagnosis and treatment purposes. A case study of gestational diabetes disease management is proposed to evaluate the effectiveness of the implemented IoT Medicare system. An evaluation phase is provided and focuses on the quality of the elaborated semantic model and the performance of the system.
机译：医疗领域的事物互联网的出现导致了大规模部署了无数的医疗连接物体（MCO）。正在开发和实施这些MCO，用于远程医疗保健监测目的，包括慢性疾病，孕妇和残疾患者的老年患者。因此，不同的相关挑战正在出现并包括来自这些MCO的聚集的健康数据的异质性，其具有不断变化的背景。这些上下文相对于MCOS部署的约束和要求的连续变化（时间，位置，状态）。其他背景与患者（医学记录，状态，年龄，性别等）有关，以确保更准确和适当治疗患者。由于没有用于描述健康数据及其来源的参考模型以及将这些数据与其上下文联系起来，因此这些挑战难以解决。本文解决了此问题，并引入了一种基于语义的上下文感知系统（IoT Medicare系统），用于使用MCOS进行患者监控。该系统基于核心域本体（HealthIOR-O），即旨在描述异构MCO的语义及其数据。此外，通过SWRL规则确保了在不同环境中的有效解释和管理，例如验证MCO的正常运作和诊断和治疗目的的健康数据的正确运作和诊断和治疗目的的正常运作。提出了对妊娠期糖尿病疾病管理的案例研究，以评估实施物有所医疗保险系统的有效性。提供评估阶段并侧重于详细的语义模型的质量和系统的性能。

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