New diagnostic tool for patients suffering from noncommunicable diseases (NCDs)

Wojciech Oleksy; Zbigniew Budzianowski; Ewaryst Tkacz; Małgorzata Garbacik

doi:10.1007/978-3-319-73450-7_45

New diagnostic tool for patients suffering from noncommunicable diseases (NCDs)

Wojciech Oleksy
, Zbigniew Budzianowski
, Ewaryst Tkacz
, Małgorzata Garbacik

Department of Medical Informatics and Artificial Intelligence (RIB/RIB1)

Silesian University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Electrocardiography, technique, which is an essential tool in the diagnosis of heart disease, as well as other organs, is used by doctors for over 100 years. It is used to measure electrical activity of the heart as a function of time and present it in digital or analogue form. Whilst the standard 12 lead ECG is the basic clinical method of heart diagnosis it has its drawbacks. Measuring all 12 leads is often difficult and impractical, most of all it restricts patient movement. In 1988, Gordon Dower developed a system of quasi-orthogonal lead called EASI, which uses only 5 electrodes in order to register standard 12 lead ECG signals. The main goal of this work is to present a new tool using machine learning algorithms which transforms electrocardiographic signals (ECG) performed by EASI into a standard 12-channel ECG, which therefore could be an ideal tool for diagnose of NCDs.

Original language	English
Title of host publication	Proceedings of the International Conference on Information Technology and Systems, ICITS 2018
Editors	Alvaro Rocha, Teresa Guarda
Publisher	Springer Verlag
Pages	476-483
Number of pages	8
ISBN (Print)	9783319734491
DOIs	https://doi.org/10.1007/978-3-319-73450-7_45
Publication status	Published - 2018
Event	International Conference on Information Technology and Systems, ICITS18 - Libertad city, Ecuador Duration: 11 Jan 2017 → 13 Jan 2017

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	721
ISSN (Print)	2194-5357

Conference

Conference	International Conference on Information Technology and Systems, ICITS18
Country/Territory	Ecuador
City	Libertad city
Period	11/01/17 → 13/01/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

EASI
ECG
Machine learning
Regression

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-319-73450-7_45

Cite this

Oleksy, W., Budzianowski, Z., Tkacz, E., & Garbacik, M. (2018). New diagnostic tool for patients suffering from noncommunicable diseases (NCDs). In A. Rocha, & T. Guarda (Eds.), Proceedings of the International Conference on Information Technology and Systems, ICITS 2018 (pp. 476-483). (Advances in Intelligent Systems and Computing; Vol. 721). Springer Verlag. https://doi.org/10.1007/978-3-319-73450-7_45

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abstract = "Electrocardiography, technique, which is an essential tool in the diagnosis of heart disease, as well as other organs, is used by doctors for over 100 years. It is used to measure electrical activity of the heart as a function of time and present it in digital or analogue form. Whilst the standard 12 lead ECG is the basic clinical method of heart diagnosis it has its drawbacks. Measuring all 12 leads is often difficult and impractical, most of all it restricts patient movement. In 1988, Gordon Dower developed a system of quasi-orthogonal lead called EASI, which uses only 5 electrodes in order to register standard 12 lead ECG signals. The main goal of this work is to present a new tool using machine learning algorithms which transforms electrocardiographic signals (ECG) performed by EASI into a standard 12-channel ECG, which therefore could be an ideal tool for diagnose of NCDs.",

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Oleksy, W, Budzianowski, Z, Tkacz, E & Garbacik, M 2018, New diagnostic tool for patients suffering from noncommunicable diseases (NCDs). in A Rocha & T Guarda (eds), Proceedings of the International Conference on Information Technology and Systems, ICITS 2018. Advances in Intelligent Systems and Computing, vol. 721, Springer Verlag, pp. 476-483, International Conference on Information Technology and Systems, ICITS18, Libertad city, Ecuador, 11/01/17. https://doi.org/10.1007/978-3-319-73450-7_45

New diagnostic tool for patients suffering from noncommunicable diseases (NCDs). / Oleksy, Wojciech; Budzianowski, Zbigniew; Tkacz, Ewaryst et al.
Proceedings of the International Conference on Information Technology and Systems, ICITS 2018. ed. / Alvaro Rocha; Teresa Guarda. Springer Verlag, 2018. p. 476-483 (Advances in Intelligent Systems and Computing; Vol. 721).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - New diagnostic tool for patients suffering from noncommunicable diseases (NCDs)

AU - Oleksy, Wojciech

AU - Budzianowski, Zbigniew

AU - Tkacz, Ewaryst

AU - Garbacik, Małgorzata

N1 - Publisher Copyright: © Springer International Publishing AG 2018.

PY - 2018

Y1 - 2018

N2 - Electrocardiography, technique, which is an essential tool in the diagnosis of heart disease, as well as other organs, is used by doctors for over 100 years. It is used to measure electrical activity of the heart as a function of time and present it in digital or analogue form. Whilst the standard 12 lead ECG is the basic clinical method of heart diagnosis it has its drawbacks. Measuring all 12 leads is often difficult and impractical, most of all it restricts patient movement. In 1988, Gordon Dower developed a system of quasi-orthogonal lead called EASI, which uses only 5 electrodes in order to register standard 12 lead ECG signals. The main goal of this work is to present a new tool using machine learning algorithms which transforms electrocardiographic signals (ECG) performed by EASI into a standard 12-channel ECG, which therefore could be an ideal tool for diagnose of NCDs.

AB - Electrocardiography, technique, which is an essential tool in the diagnosis of heart disease, as well as other organs, is used by doctors for over 100 years. It is used to measure electrical activity of the heart as a function of time and present it in digital or analogue form. Whilst the standard 12 lead ECG is the basic clinical method of heart diagnosis it has its drawbacks. Measuring all 12 leads is often difficult and impractical, most of all it restricts patient movement. In 1988, Gordon Dower developed a system of quasi-orthogonal lead called EASI, which uses only 5 electrodes in order to register standard 12 lead ECG signals. The main goal of this work is to present a new tool using machine learning algorithms which transforms electrocardiographic signals (ECG) performed by EASI into a standard 12-channel ECG, which therefore could be an ideal tool for diagnose of NCDs.

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Oleksy W, Budzianowski Z, Tkacz E, Garbacik M. New diagnostic tool for patients suffering from noncommunicable diseases (NCDs). In Rocha A, Guarda T, editors, Proceedings of the International Conference on Information Technology and Systems, ICITS 2018. Springer Verlag. 2018. p. 476-483. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-73450-7_45

New diagnostic tool for patients suffering from noncommunicable diseases (NCDs)

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this