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Self-awareness in remote health monitoring systems using wearable electronics

机译:使用可穿戴电子设备的远程健康监控系统中的自我意识

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In healthcare, effective monitoring of patients plays a key role in detecting health deterioration early enough. Many signs of deterioration exist as early as 24 hours prior having a serious impact on the health of a person. As hospitalization times have to be minimized, in-home or remote early warning systems can fill the gap by allowing in-home care while having the potentially problematic conditions and their signs under surveillance and control. This work presents a remote monitoring and diagnostic system that provides a holistic perspective of patients and their health conditions. We discuss how the concept of self-awareness can be used in various parts of the system such as information collection through wearable sensors, confidence assessment of the sensory data, the knowledge base of the patient's health situation, and automation of reasoning about the health situation. Our approach to self-awareness provides (i) situation awareness to consider the impact of variations such as sleeping, walking, running, and resting, (ii) system personalization by reflecting parameters such as age, body mass index, and gender, and (iii) the attention property of self-awareness to improve the energy efficiency and dependability of the system via adjusting the priorities of the sensory data collection. We evaluate the proposed method using a full system demonstration.
机译:在医疗保健中,对患者的有效监控在及早发现健康恶化方面起着关键作用。早在对人的健康产生严重影响之前的24小时,就存在许多恶化的迹象。由于必须将住院时间减至最少,因此,在允许处于潜在问题状态及其迹象受到监视和控制的同时,可以通过允许进行家庭护理来填补家庭或远程预警系统的空白。这项工作提出了一个远程监视和诊断系统,该系统提供了患者及其健康状况的整体视角。我们讨论如何在系统的各个部分中使用自我意识的概念,例如通过可穿戴式传感器收集信息,对感官数据进行置信度评估,患者健康状况的知识库以及有关健康状况的推理自动化。我们的自我认知方法提供(i)情境意识,以考虑诸如睡眠,行走,跑步和休息之类的变化的影响;(ii)通过反映年龄,体重指数和性别等参数来实现系统个性化,以及( iii)通过调整感官数据收集的优先级来提高系统的能源效率和可靠性的自我意识的注意力属性。我们使用完整的系统演示评估提出的方法。

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