TY  - JOUR
AU  - Vićentić, Teodora
AU  - Rašljić Rafajilović, Milena
AU  - Ilić, Stefan
AU  - Koteska, Bojana
AU  - Madevska Bogdanova, Ana
AU  - Pašti, Igor
AU  - Lehocki, Fedor
AU  - Spasenović, Marko
PY  - 2022
UR  - https://cer.ihtm.bg.ac.rs/handle/123456789/5559
AB  - The 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.
PB  - MDPI AG
T2  - Sensors
T1  - Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis
VL  - 22
IS  - 17
SP  - 6326
DO  - 10.3390/s22176326
ER  - 

@article{
author = "Vićentić, Teodora and Rašljić Rafajilović, Milena and Ilić, Stefan and Koteska, Bojana and Madevska Bogdanova, Ana and Pašti, Igor and Lehocki, Fedor and Spasenović, Marko",
year = "2022",
abstract = "The 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.",
publisher = "MDPI AG",
journal = "Sensors",
title = "Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis",
volume = "22",
number = "17",
pages = "6326",
doi = "10.3390/s22176326"
}

Vićentić, T., Rašljić Rafajilović, M., Ilić, S., Koteska, B., Madevska Bogdanova, A., Pašti, I., Lehocki, F.,& Spasenović, M.. (2022). Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis. in Sensors
MDPI AG., 22(17), 6326.
https://doi.org/10.3390/s22176326

Vićentić T, Rašljić Rafajilović M, Ilić S, Koteska B, Madevska Bogdanova A, Pašti I, Lehocki F, Spasenović M. Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis. in Sensors. 2022;22(17):6326.
doi:10.3390/s22176326 .

Vićentić, Teodora, Rašljić Rafajilović, Milena, Ilić, Stefan, Koteska, Bojana, Madevska Bogdanova, Ana, Pašti, Igor, Lehocki, Fedor, Spasenović, Marko, "Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis" in Sensors, 22, no. 17 (2022):6326,
https://doi.org/10.3390/s22176326 . .