Use of telecommunication technologies for remote, continuous monitoring of patients can enhance e ectiveness 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 uctuation together with real-time communication of various clinical multimedia pose a major challenge during rural patient ambulance transport. e 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 pro ling 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 pro ler, 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 ality of Service (QoS) for most critical clinical multimedia in response to changes in patients' physiological states and bandwidth conditions. Our dataset is available online 1 for research community. CCS CONCEPTS•Networks →Network measurement; KEYWORDSPhysiology-aware DASH, network pro ling, bandwidth, GPS 1 h p
Abstract-The ultimate objective of medical cyber-physical systems is to enhance the safety and effectiveness of patient care. To ensure safe and effective care during emergency patient transfer from rural areas to center tertiary hospitals, reliable and real-time communication is essential. Unfortunately, real-time monitoring of patients involves transmission of various clinical multimedia data including videos, medical images, and vital signs, which requires use of mobile network with high-fidelity communication bandwidth. However, the wireless networks along the roads in rural areas range from 4G to 2G to low speed satellite links, which poses a significant challenge to transmit critical patient information.In this paper, we present a bandwidth-compliant criticalityaware system for transmission of massive clinical multimedia data adaptive to varying bandwidths during patient transport. Model-based clinical automata are used to determine the criticality of clinical multimedia data. We borrow concepts from DASH, and propose physiology-aware adaptation techniques to transmit more critical clinical data with higher fidelity in response to changes in disease, clinical states, and bandwidth condition. In collaboration with Carle's ambulance service center, we develop a bandwidth profiler, and use it as proof of concept to support our experiments. Our preliminary evaluation results show that our solutions ensure that most critical patient's clinical data are communicated with higher fidelity. ACKNOWLEDGMENTThis paper reviews a technology package that is the result of a team effort. Lui Sha led the development of model-driven multimedia clinical systems and all system integration. Yu Jiang and Houbing Song helped with the development of physiological and cyber-physical models. Richard Berlin guided the study of patient emergency care, physiological multimedia data, and medical correctness. Mohammad Hosseini led the design and development of the multimedia communication system, adaptation system, heuristic algorithms, as well as development of the profiler app and conducting experiments and evaluations.
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