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基于SPN模型的可穿戴健康监测系统仿真

SPN-model based simulation of a wearable health monitoring system.

作者信息

Pantelopoulos Alexandros, Bourbakis Nikolaos

机构信息

Assistive Technologies Research Center, Wright State University, Dayton, Ohio 45435, USA.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:320-3. doi: 10.1109/IEMBS.2009.5333786.

Abstract

The deployment of Wearable Health Monitoring Systems (WHMS) can potentially enable ubiquitous and continuous monitoring of a patient's physiological parameters. Moreover by incorporating multiple biosensors in such a system a comprehensive estimation of the user's health condition can possibly be derived. In this paper we present a Stochastic Petri Net (SPN) model of a multi-sensor WHMS along with a corresponding simulation framework implemented in Java. The proposed model is built on top of a previously published multisensor data fusion strategy, which has been expanded in this work to take into account synchronization issues and temporal dependencies between the measured bio-signals.

摘要

可穿戴健康监测系统(WHMS)的部署有可能实现对患者生理参数的普遍和持续监测。此外,通过在这样一个系统中集成多个生物传感器,有可能得出对用户健康状况的全面评估。在本文中,我们提出了一种多传感器WHMS的随机Petri网(SPN)模型以及一个用Java实现的相应模拟框架。所提出的模型是基于先前发表的多传感器数据融合策略构建的,在这项工作中该策略已得到扩展,以考虑测量的生物信号之间的同步问题和时间依赖性。

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