Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis
Journal
Sensors
Date Issued
2022-08-23
Author(s)
Vićentić, Teodora
Rašljić Rafajilović, Milena
Ilić, Stefan
Madevska Bogdanova, Ana
Pašti, Igor
Lehocki, Fedor
Spasenović, Marko
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.
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.
Subjects
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