Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12188/29151
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Madevska Bogdanova, Ana | en_US |
dc.contributor.author | Koteska, Bojana | en_US |
dc.contributor.author | Vićentić, Teodora | en_US |
dc.contributor.author | D. Ilić, Stefan | en_US |
dc.contributor.author | Tomić, Miona | en_US |
dc.contributor.author | Spasenović, Marko | en_US |
dc.date.accessioned | 2024-02-01T21:00:58Z | - |
dc.date.available | 2024-02-01T21:00:58Z | - |
dc.date.issued | 2024-01-29 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12188/29151 | - |
dc.description.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. | en_US |
dc.description.sponsorship | NATO Science for Peace and Security Program | en_US |
dc.language.iso | en | en_US |
dc.publisher | Hindawi Limited | en_US |
dc.relation | SP4LIFE, number G5825 | en_US |
dc.relation.ispartof | Journal of Sensors | en_US |
dc.relation.ispartofseries | ;4696031 | - |
dc.subject | Oxygen saturation | en_US |
dc.subject | Machine Learning | en_US |
dc.subject | Graphene | en_US |
dc.subject | Sensor | en_US |
dc.title | Blood Oxygen Saturation Estimation with Laser-Induced Graphene Respiration Sensor | en_US |
dc.type | Journal Article | en_US |
dc.identifier.doi | 10.1155/2024/4696031 | - |
dc.identifier.url | http://downloads.hindawi.com/journals/js/2024/4696031.pdf | - |
dc.identifier.url | http://downloads.hindawi.com/journals/js/2024/4696031.xml | - |
dc.identifier.url | http://downloads.hindawi.com/journals/js/2024/4696031.pdf | - |
dc.identifier.volume | 2024 | - |
item.grantfulltext | open | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
crisitem.author.dept | Faculty of Computer Science and Engineering | - |
Appears in Collections: | Faculty of Computer Science and Engineering: Journal Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
4696031.pdf | 3.27 MB | Adobe PDF | View/Open |
Page view(s)
31
checked on May 15, 2024
Download(s)
2
checked on May 15, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.