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A formal language approach for multi-sensor Wearable Health-Monitoring Systems

机译:多传感器可穿戴健康监测系统的正式语言方法

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摘要

Wearable Health-Monitoring Systems (WHMS) promise to revolutionize health care by providing real-time unobtrusive monitoring of patients’ physiological parameters through the deployment of several on-body and even intra-body biosensors. Although several technological issues regarding WHMS still need to be resolved, in order for them to become more applicable in real-life scenarios, it is expected that continuous ambulatory monitoring of vital signs will enable pro-active personal health management and better treatment of patients suffering from chronic diseases, of the elderly population and of emergency situations. In this paper a novel formal language based model for multi-sensor data fusion and early-detection of various conditions is presented. Patterns or even signal states indicating pathological symptoms that are presented in the signals, which can be collected from on-body distributed biosensors, are modeled as symbols of the Prognosis context-free formal language, whose grammar and production rules define the prognosis-words. The proposed approach is based on a described generic WHMS model and on a simple but at the same time efficient method for characterizing body-signal’s patterns and/or states. Finally, we provide several illustrative examples for better comprehension of the proposed model.
机译:可穿戴的健康监测系统(WHMS)承诺通过部署几个身体和均匀的体传感器来提供对患者生理参数的实时不引人注目的监测来彻底改变医疗保健。虽然有关WHMS的几个技术问题仍然需要解决,但是为了让他们更适用于现实生活场景,预计对生命体征的持续矛盾监测将实现积极的个人健康管理,并更好地治疗患者患者来自老年人的慢性病和紧急情况。本文介绍了一种基于新型的多传感器数据融合和各种条件的早期检测的基于形式的基于语言模型。表明在可以从体分布的生物传感器中收集的信号中呈现的病理症状的模式或偶数信号状态被建模为预后无论如何的正式语言的符号,其语法和生产规则定义预后词。所提出的方法基于所描述的通用WHMS模型,并且在简单但是以同时的时间有效的方法,用于表征身体信号的模式和/或状态。最后,我们提供了几个说明性的例子,以便更好地理解所提出的模型。

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