Development of instrumented bed monitoring system

Chan, Mercedes Simh Peh (2023) Development of instrumented bed monitoring system. Final Year Project, UTAR.

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Abstract

Numerous distressing Hospital-Acquired Conditions (HACs), such as falls, and pressure injuries, predominantly occur within the vicinity of the hospital bed. Despite much effort, these conditions are still prevalent today. Current prevention practices for these HACs involve a combination of staff protocol and technological assistive devices. However, these measures have a heavy reliance on the medical staff, with vulnerabilities exacerbated by staff shortages, especially in overcrowded medical facilities. Henceforth, this project aims to develop an instrumented bed monitoring system that can function as a bed-exit alarm whilst mitigating pressure injuries via the continuous monitoring of movement. The system is comprised of a central processing unit, touchscreen user interface and a multilayered sensor array, in the form of a mattress protector sheet. The sensor sheet is a qualitative pressure array consisting of 128 points, arranged in an eight by sixteen matrix and features two layers: one with eight vertical sensing lines and the other with sixteen horizontals. These sensor lines are thin stainless-steel wires sewn into cloth with the help of a sewing machine and have proven to be incredibly sensitive to touch. Scanning of the array is done in real time, allowing for continuous monitoring of the patient’s status. Moreover, the patient status can be viewed on the colour touchscreen at the bedside terminal or remotely through a web browser on a computer or handphone. Ultimately, the nurses will be notified when anomalies are identified, and the alarms are triggered. These are instances such as the absence of bodily movement for more than 2 hours or when the patient moves to make an unauthorised exit off the bed, enabling timely interventions, where in this case it is to either reposition the patient to prevent bed sores or aid the frail patients from falling. The current project prototype can effectively detect items that are heavier than 350g in weight and is 70.3% accurate in reproducing the sleeping profile of the user on the instrumented bed. Although more work is required to improve the bed array sensing accuracy, the system has no issues performing its intended functions in mitigating preventable suffering caused by HACs, as proven by the high efficacy rates of the alarms and alerts.

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