Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/22661
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dc.contributor.authorVićentić, Teodoraen_US
dc.contributor.authorRašljić Rafajilović, Milenaen_US
dc.contributor.authorIlić, Stefanen_US
dc.contributor.authorKoteska, Bojanaen_US
dc.contributor.authorMadevska Bogdanova, Anaen_US
dc.contributor.authorPašti, Igoren_US
dc.contributor.authorLehocki, Fedoren_US
dc.date.accessioned2022-08-29T08:01:10Z-
dc.date.available2022-08-29T08:01:10Z-
dc.date.issued2023-08-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/22661-
dc.description.abstractThe HeartPy Python toolkit for analysis of noisy signals from heart rate measurements is an excellent tool to use in conjunction with novel wearable sensors. Nevertheless, most of the work to date has focused on applying the toolkit to data measured with commercially available sensors. We demonstrate the application of the HeartPy functions to data obtained with a novel graphene-based heartbeat sensor. We produce the sensor by laser-inducing graphene on a flexible polyimide substrate. Both graphene on the polyimide substrate and graphene transferred onto a PDMS substrate show piezoresistive behavior that can be utilized to measure human heartbeat by registering median cubital vein motion during blood pumping. We process electrical resistance data from the graphene sensor using HeartPy and demonstrate extraction of several heartbeat parameters, in agreement with measurements taken with independent reference sensors. We compare the quality of the heartbeat signal from graphene on different substrates, demonstrating that in all cases the device yields results consistent with reference sensors. Our work is a first demonstration of successful application of HeartPy to analysis of data from a sensor in development.en_US
dc.language.isoen_USen_US
dc.publisherSensorsen_US
dc.relation.ispartofseries22(17);6326-
dc.subjectbioinformaticsen_US
dc.subjectbiomedical electronicsen_US
dc.subjectbiomedical materialsen_US
dc.subjectbiomedical signal processingen_US
dc.subjectbiosensorsen_US
dc.subjectmedical information systemsen_US
dc.subjectwearable sensorsen_US
dc.titleLaser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysisen_US
dc.typeJournal Articleen_US
dc.identifier.doi10.3390/s22176326-
item.grantfulltextnone-
item.fulltextNo Fulltext-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
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