农村救护车运输中生理感知DASH的移动地理通信数据集

Mohammad Hosseini, Yu Jiang, Ali Yekkehkhany, R. E. Berlin, L. Sha
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引用次数: 16

摘要

利用电信技术对患者进行远程、持续监测,可以提高从农村地区到区域中心医院的急救护理的有效性。然而,在农村地区沿各种路由的通信可能具有2G至4G的宽带宽范围;有些地区可能只有较低的卫星带宽可用。带宽波动和各种临床多媒体的实时通信是农村病人救护车运输的主要挑战。AB@The传输前路径相关的通信带宽数据库的可用性是农村救护车运输中远程监测和临床多媒体传输的重要资源。在这里,我们展示了一个地理通信数据集,该数据集来自伊利诺伊州4家主要的美国移动运营商的广泛分析,从霍普斯顿的农村地区到厄巴纳的中央转诊医院中心。我们与卡尔基金会医院合作,开发了一个侧写器,并收集了各种地理和通信痕迹,用于现实的紧急农村救护车运输场景。我们的数据集是为了支持我们正在进行的提出“生理感知DASH”的工作,这对于紧急农村救护车运输中危重患者的自适应远程监测特别有用。它为大多数关键的临床多媒体确保更高的服务质量(QoS)以响应患者生理状态和带宽条件的变化提供了见解。我们的数据集可在线获取1供研究社区使用。
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A Mobile Geo-Communication Dataset for Physiology-Aware DASH in Rural Ambulance Transport
Use of telecommunication technologies for remote, continuous monitoring of patients can enhance effectiveness of emergency ambulance care during transport from rural areas to a regional center hospital. However, the communication along the various routes in rural areas may have wide bandwidth ranges from 2G to 4G; some regions may have only lower satellite bandwidth available. Bandwidth fluctuation together with real-time communication of various clinical multimedia pose a major challenge during rural patient ambulance transport.; AB@The availability of a pre-transport route-dependent communication bandwidth database is an important resource in remote monitoring and clinical multimedia transmission in rural ambulance transport. Here, we present a geo-communication dataset from extensive profiling of 4 major US mobile carriers in Illinois, from the rural location of Hoopeston to the central referral hospital center at Urbana. In collaboration with Carle Foundation Hospital, we developed a profiler, and collected various geographical and communication traces for realistic emergency rural ambulance transport scenarios. Our dataset is to support our ongoing work of proposing "physiology-aware DASH", which is particularly useful for adaptive remote monitoring of critically ill patients in emergency rural ambulance transport. It provides insights on ensuring higher Quality of Service (QoS) for most critical clinical multimedia in response to changes in patients' physiological states and bandwidth conditions. Our dataset is available online1 for research community.
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