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Наслов: Blood Oxygen Saturation Estimation with Laser-Induced Graphene Respiration Sensor
Authors: Madevska Bogdanova, Ana 
Koteska, Bojana 
Vićentić, Teodora
D. Ilić, Stefan
Tomić, Miona
Spasenović, Marko
Keywords: Oxygen saturation
Machine Learning
Graphene
Sensor
Issue Date: 29-јан-2024
Publisher: Hindawi Limited
Проект: SP4LIFE, number G5825
Journal: Journal of Sensors
Series/Report no.: ;4696031
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.
URI: http://hdl.handle.net/20.500.12188/29151
DOI: 10.1155/2024/4696031
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles

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