自主、连续、实时患者监测的物联网系统及其在压力损伤管理中的应用

Sam Mansfield, Eric Vin, K. Obraczka
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引用次数: 1

摘要

在本文中,我们介绍了PIMAP,这是一种基于物联网的系统,用于以完全自主的方式进行连续、实时的患者监测,即不需要人为干预。据我们所知,PIMAP是第一个集成了基本患者监测工作流程的开放系统,包括感测数据收集、存储、分析和实时可视化。PIMAP的开放式设计允许它轻松集成各种传感器(定制的和现成的)、分析和可视化。PIMAP的其他新特性包括其部署灵活性,即根据特定的应用程序需求、设置和资源以不同配置进行部署的能力,以及PIMAP的自分析和自调优功能。虽然PIMAP可以应用于各种患者监测应用和设置,但在本文中,我们侧重于预防压疮或压伤的未解决问题。我们描述了PIMAP的设计如何解决自主、连续、实时的操作,以感知、存储、分析和可视化来自各种现成和定制传感器的患者数据。我们展示了当前的PIMAP原型以及不同的PIMAP配置场景,例如基于云的或基于边缘的部署选项。我们还评估了PIMAP在不同工作负荷下的性能,并演示了其在现实场景中收集可穿戴压力传感器数据的用途,这些数据来自形成压力损伤的高风险患者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An IoT System for Autonomous, Continuous, Real-Time Patient Monitoring and Its Application to Pressure Injury Management
In this paper, we introduce PIMAP, an IoT-based system for continuous, real-time patient monitoring that operates in a fully autonomous fashion, i.e. without the need for human intervention. To our knowledge, PIMAP is the first open system that integrates the basic patient monitoring workflow including sensed data collection, storage, analysis, and real-time visualization. PIMAP's open design allows it to easily integrate a variety of sensors (custom and off-the-shelf), analytics, and visualization. Other novel features of PIMAP include its deployment flexibility, i.e., its ability to be deployed in different configurations depending on the specific application needs, setting, and resources, as well as PIMAP's self-profiling and self-tuning capabilities. While PIMAP can be applied to various patient monitoring applications and settings, in this paper we focus on the unsolved problem of preventing pressure ulcers, or pressure injuries. We describe how PIMAP's design addresses autonomous, continuous, realtime operation to sense, store, analyze, and visualize patient data from a variety of off-the-shelf as well as custom sensors. We present our current PIMAP prototype as well as different PIMAP configuration scenarios, e.g. cloud-based or edge-based deployment options. We also evaluate PIMAP's performance under different workloads and demonstrate its use collecting wearable pressure sensor data in real-world scenarios from patients with high risk of forming pressure injuries.
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