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Full Impedance Cardiography measurement device using Raspberry PI3 and System-on-Chip biomedical Instrumentation Solutions
University of Borås, Faculty of Textiles, Engineering and Business. University of Sciences and Technology Houari Boumediene.
University of Borås, Faculty of Textiles, Engineering and Business.
University of Sciences and Technology Houari Boumediene.
Karolinska Institutet.ORCID iD: 0000-0001-7807-8682
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2017 (English)In: IEEE journal of biomedical and health informatics, ISSN 2168-2194, E-ISSN 2168-2208Article in journal (Refereed) Published
Abstract [en]

Impedance Cardiography (ICG) is a non-invasive method for monitoring cardiac dynamics using Electrical Bioimpedance (EBI) measurements. Since its appearance more than 40 years ago, ICG has been used for assessing hemodynamic parameters. This paper present a measurement system based on two System on Chip (SoC) solutions and Raspberry PI, implementing both a full 3-lead ECG recorder and an impedance cardiographer, for educational and research development purposes. Raspberry PI is a platform supporting Do-It-Yourself project and education applications across the world. The development is part of Biosignal PI, an open hardware platform focusing in quick prototyping of physiological measurement instrumentation. The SoC used for sensing cardiac biopotential is the ADAS1000, and for the EBI measurement is the AD5933. The recording were wirelessly transmitted through Bluetooth to a PC, where the waveforms were displayed, and hemodynamic parameters such as heart rate, stroke volume, ejection time and cardiac output were extracted from the ICG and ECG recordings. These results show how Raspberry PI can be used for quick prototyping using relatively widely available and affordable components, for supporting developers in research and engineering education. The design and development documents, will be available on www.BiosignalPI.com, for open access under a Non Commercial-Share A like 4.0 International License.

Place, publisher, year, edition, pages
IEEE , 2017.
National Category
Medical Engineering
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URN: urn:nbn:se:hb:diva-13769DOI: 10.1109/JBHI.2017.2783949OAI: oai:DiVA.org:hb-13769DiVA, id: diva2:1187341
Available from: 2018-03-03 Created: 2018-03-03 Last updated: 2018-03-20Bibliographically approved

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Seoane, Fernando

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