Subject: Oxygen saturation
Subject: Machine Learning
Subject: Graphene
Subject: Sensor
Year: 2024
Type: Journal Article
Title: Blood Oxygen Saturation Estimation with Laser-Induced Graphene Respiration Sensor
Author: Madevska Bogdanova, Ana
Author: Koteska, Bojana
Author: Vićentić, Teodora
Author: D. Ilić, Stefan
Author: Tomić, Miona
Author: Spasenović, Marko
Abstract: Measuring blood oxygen saturation (SpO2) is crucial in a triage process for identifying patients with respiratory distress or shock, since low SpO2 levels indicate compromised hemostability and the need for priority treatment. This paper explores the use of wearable mechanical deflection sensors based on laser-induced graphene (LIG) for SpO2 estimation. The LIG sensors are attached to a subject’s chest for real-time monitoring of respiratory signals. We have developed a novel database of the respiratory signals, with corresponding SpO2 values ranging from 86% to 100%. The database is used to develop an artificial neural network model for SpO2 estimation. The neural network performance is promising, with regression metrics mean squared error = 0.184, mean absolute error = 0.301, root mean squared error = 0.429, and R-squared = 0.804. The use of mechanical respiration sensors in combination with neural networks in biosensing opens new possibilities for noninvasive SpO2 monitoring and other innovative applications.
Publisher: Hindawi Limited
Relation: SP4LIFE, number G5825
Identifier: oai:repository.ukim.mk:20.500.12188/29151
Identifier: http://hdl.handle.net/20.500.12188/29151Identifier: 10.1155/2024/4696031
Identifier: http://downloads.hindawi.com/journals/js/2024/4696031.pdfIdentifier: http://downloads.hindawi.com/journals/js/2024/4696031.xmlIdentifier: http://downloads.hindawi.com/journals/js/2024/4696031.pdfIdentifier: 2024
