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Pulse rhythm

Pulse rhythm

Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac...

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Related Experiment Video

Updated: Aug 29, 2025

Semi-automated Optical Heartbeat Analysis of Small Hearts

Semi-automated Optical Heartbeat Analysis of Small Hearts

Published on: September 16, 2009

Laser-Induced Graphene for Heartbeat Monitoring with HeartPy Analysis.

Teodora Vićentić¹, Milena Rašljić Rafajilović¹, Stefan D Ilić¹

¹Center for Microelectronic Technologies, Institute of Chemistry, Technology and Metallurgy, National Institute of the Republic of Serbia, University of Belgrade, 11000 Belgrade, Serbia.

Sensors (Basel, Switzerland)

|September 9, 2022

Summary

This study shows how the HeartPy Python toolkit can analyze data from a new graphene-based heartbeat sensor. The novel sensor, using piezoresistive graphene, accurately measures heartbeat parameters, validated against reference devices.

Keywords:

bioinformatics biomedical electronics biomedical materials biomedical signal processing biosensors medical information systems programming software performance wearable sensors

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Area of Science:

Biomedical Engineering
Materials Science
Wearable Technology

Background:

The HeartPy Python toolkit is valuable for analyzing noisy heart rate data from wearable sensors.
Existing research primarily uses HeartPy with commercially available sensors.
Novel sensors require validation with established analysis tools.

Purpose of the Study:

To demonstrate the application of the HeartPy toolkit with a novel graphene-based heartbeat sensor.
To validate the performance of a new graphene sensor for heartbeat detection.
To assess the compatibility of HeartPy with developing sensor technologies.

Main Methods:

Fabrication of a graphene-based heartbeat sensor using laser-induced graphene on flexible substrates (polyimide and PDMS).
Measurement of heartbeat by detecting piezoresistive changes in graphene due to median cubital vein motion.
Processing of electrical resistance data using the HeartPy Python toolkit.
Comparison of HeartPy-derived heartbeat parameters with data from independent reference sensors.

Main Results:

The graphene-based sensor, on both polyimide and PDMS substrates, exhibited piezoresistive behavior suitable for heartbeat detection.
HeartPy successfully processed sensor data, extracting key heartbeat parameters consistent with reference measurements.
Signal quality from the graphene sensor was comparable across different substrates and validated by reference sensors.

Conclusions:

This work represents the first successful application of the HeartPy toolkit to analyze data from a developing graphene-based heartbeat sensor.
The novel graphene sensor shows promise for accurate heartbeat monitoring when analyzed with established tools like HeartPy.
The findings support the integration of advanced materials and analysis software for next-generation wearable health devices.