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Advanced 4.0 Bed Management System, embedded with IoT, Digital Twins and, Cyber Physical System
  • Marco Mosca,
  • Roberto Mosca,
  • Federico Briatore
Marco Mosca
DIME, University of Genoa
Roberto Mosca
DIME, University of Genoa
Federico Briatore
DIME, University of Genoa

Corresponding Author:[email protected]

Author Profile

Abstract

Objective: the paper aims to address the surveillance of long-term bedridden patients. Although often necessary, continuous monitoring cannot be carried out due to cost constraints and limited personnel availability. Current solutions involve wearable devices and cameras, but they have limitations, as discomfort and concerns about privacy. Method: firstly, a thorough review of existing literature has been carried out. Then, it was developed the innovative system, focusing on bed monitoring instead of direct patient control. After identifying necessary patient condition data, various sensors were tested. To leverage data potential, the authors explored methods of centralizing and analyzing information. A platform was designed to assist operators in anticipating accidents. Finally, Digital Twins and Cyber Physical Systems were considered for their potential value in the system. Results: The proposed system monitors patient's bed without direct contact, in contrast to wearable devices. This innovative approach utilizes applied sensors capable of identifying risky behaviors, signs of specific pathologies, unusual movements, tremors, or abnormal humidity in the bed. The benefits include improved service levels, reduced operator surveillance, freeing up time for value-added activities, timely intervention where necessary, prevention of bed falls and sores, detection of wet beds, enhancement of sleep quality, and monitoring of weight trends. Conclusions: Literature indicates that lack of bed surveillance in healthcare is a global issue expected to worsen due to the progressive aging of the population. Authors’ 4.0 solution can effectively address this problem, improving service levels by monitoring and simulating patient behavior rather than direct monitoring, thus minimizing patient discomfort.
24 May 2024Submitted to TechRxiv
30 May 2024Published in TechRxiv