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Real-time Tracking of Medical Devices: An Analysis of Multilateration and Fingerprinting Approaches (preprint)
arxiv; 2023.
Preprint in English | PREPRINT-ARXIV | ID: ppzbmed-2303.01151v1
ABSTRACT
Hospital infrastructures are always in evidence in periods of crisis, such as natural disasters or pandemic events, under stress. The recent COVID-19 pandemic exposed several inefficiencies in hospital systems over a relatively long period. Among these inefficiencies are human factors, such as how to manage staff during periods of high demand, and technical factors, including the management of Portable Medical Devices (PMD), such as mechanical ventilators, capnography monitors, infusion pumps, or pulse oximeters. These devices, which are vital for monitoring patients or performing different procedures, were found to have a high turnover during high-demand, resulting in inefficiencies and more pressure on medical teams. Thus, the work PMD-Track evaluates in detail two popular indoor tracking approaches concerning their accuracy, placement of beacons, and economic impacts. The key novelty of PMD-Track relies on using smartphones provided to hospital employees, replacing typical stationary gateways spread across a hospital, functioning as mobile gateways with a front-end that assists staff in locating PMDs. As employees approach tagged PMDs, their smartphone automatically updates the location of spotted PMDs in real-time, providing room-level localization data with up to 83% accuracy for fingerprinting and 35% for multilateration. In addition, fingerprinting is 45% cheaper than multilateration over the course of five years. Practical experiments were evaluated based on two locations in Z\"urich, Switzerland.
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Full text: Available Collection: Preprints Database: PREPRINT-ARXIV Main subject: Neuromyelitis Optica / COVID-19 Language: English Year: 2023 Document Type: Preprint

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Full text: Available Collection: Preprints Database: PREPRINT-ARXIV Main subject: Neuromyelitis Optica / COVID-19 Language: English Year: 2023 Document Type: Preprint