Cardiac Ischemia Detection Using Parameters Extracted from the Intrinsic Mode Functions

Authors

  • Carolina Fernández Biscay Instituto Argentino de Matemática "Alberto P. Calderón", CONICET, Ciudad Autónoma de Buenos Aires, Argentina. Instituto de Ingeniería Biomédica, Facultad de Ingeniería, Universidad de Buenos Aires, Argentina. https://orcid.org/0000-0002-8982-6399
  • María Paula Bonomini Instituto Argentino de Matemática "Alberto P. Calderón", CONICET, Ciudad Autónoma de Buenos Aires, Argentina. Instituto de Ingeniería Biomédica, Facultad de Ingeniería, Universidad de Buenos Aires, Argentina. https://orcid.org/0000-0002-0351-2568
  • Miguel Eduardo Zitto Facultad de Ingeniería, Universidad de Buenos Aires, Argentina. Universidad Tecnológica Nacional, Regional Buenos Aires, Buenos Aires, Argentina. https://orcid.org/0000-0002-6423-1719
  • Rosa Piotrkowski Instituto de Tecnologías Emergentes y Ciencias Aplicadas (ITECA), UNSAM-CONICET, Argentina. Escuela de Ciencia y Tecnología, Centro de Matemática Aplicada (CEDEMA), Argentina Facultad de Ingeniería, Universidad de Buenos Aires, Argentina. https://orcid.org/0000-0002-6004-5679
  • Pedro David Arini Instituto Argentino de Matemática "Alberto P. Calderón", CONICET, Ciudad Autónoma de Buenos Aires, Argentina. Instituto de Ingeniería Biomédica, Facultad de Ingeniería, Universidad de Buenos Aires, Argentina. https://orcid.org/0000-0002-5548-7528

Keywords:

Electrocardiogram, Empirical Mode Decomposition, Hilbert Transform, Hjorth Activity

Abstract

Cardiac ischemia is the main cause of death in the world, thus the importance of prevention and early detection of these events. Traditionally, ischemia is detected by analyzing the alteration of the ST level in the electrocardiogram (ECG). In this study, we propose two new parameters extracted from the ECG to improve the cardiac ischemia detection. For this, the signal was decomposed using the Empirical Mode Decomposition, and the Intrinsic Mode Functions related to the frequency band of the ST level were selected. From these modes, two parameters were obtained: the Hjorth Activity and the frequency amplitude, using the Hilbert Transform. With these parameters, two analyses were done. First, the parameters obtained during normal periods were compared with those obtained during ischemic events. Second, a temporal series was obtained with both parameters, where the detection was done using an adaptative threshold. Results were obtained using all the patients with MLIII lead of the European ST-T Database. Parameters differed significantly across ischemic and non ischemic episodes, obtaining a sensitivity and positive predictive value of 88%, after removing noisy records. Also, a multi-lead detection was performed in patients with MLIII and V4 leads. The sensitivity and positive predictive value obtained were 92% and 80%, respectively.

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Author Biographies

Carolina Fernández Biscay, Instituto Argentino de Matemática "Alberto P. Calderón", CONICET, Ciudad Autónoma de Buenos Aires, Argentina. Instituto de Ingeniería Biomédica, Facultad de Ingeniería, Universidad de Buenos Aires, Argentina.

Carolina Fernández Biscay was born in Argentina in 1989. She received the biomedical engineering degree in 2013 from Favaloro University, Buenos Aires, Argentina. Afterwards, she worked in the clinical engineering area of Hospital Alemán (Buenos Aires, Argentina). In 2016, she was awarded with a PhD scholarship by the National Council for Scientific and Technical Research (CONICET, Argentina). Since then, she is doing the PhD in engineering in Buenos Aires University (Argentina). Her research is done in Cardio-Signals Research Group at the Argentine Institute of Mathematics, “Alberto P. Calderon” and at the Biomedical Engineering Institute of the Engineering Faculty from the Buenos Aires University. Her current research interests include cardiac diseases (in particular ischemia), signal processing (especially on electrocardiogram records) and classification analysis.

María Paula Bonomini, Instituto Argentino de Matemática "Alberto P. Calderón", CONICET, Ciudad Autónoma de Buenos Aires, Argentina. Instituto de Ingeniería Biomédica, Facultad de Ingeniería, Universidad de Buenos Aires, Argentina.

María Paula Bonomini was born in San Jorge, Argentina, in 1977. In 2001, she received M.S. degree in bioengineering from the National University of Entre Ríos, Argentina. In 2010, she obtained the PhD degree in Bioengineering from the University Miguel Hernandez of Elche, Spain. Since then, she worked in cardiac electrophysiology and ECG signal processing.
Since 2013, she has been a Research Scientist of the National Council for Scientific and Technical Research (CONICET) and develops her work in the Cardio-Signals Research Group at the Argentine Institute of Mathematics “Alberto P. Calderon”. Since 2013, she has been auxiliary professor of Signals and Images in Biomedicine at the Biomedical Engineering Institute of the Engineering Faculty from the Buenos Aires University (UBA). She published more than 15 scientific articles in international journals and her research interests involve biomedical signal processing.

Miguel Eduardo Zitto, Facultad de Ingeniería, Universidad de Buenos Aires, Argentina. Universidad Tecnológica Nacional, Regional Buenos Aires, Buenos Aires, Argentina.

Miguel Eduardo Zitto was born in 1961 in Buenos Aires, Argentina. In 1997 he obtained a Bachelor's degree in physical sciences and in 2004 a master's degree in Numerical Simulation and Control. Both degrees where obtained in Universidad de Buenos Aires, Argentina. Since 2006 he has been working in Universidad de Buenos Aires, where he is currently Co-director of the research group Analysis of Non-stationary and Non-linear Time Series. He published more than 10 scientific articles in international journals, and his current topics of interest are the analysis of non-stationary and non-linear time series applied to climatological series of acoustic emission.

Rosa Piotrkowski, Instituto de Tecnologías Emergentes y Ciencias Aplicadas (ITECA), UNSAM-CONICET, Argentina. Escuela de Ciencia y Tecnología, Centro de Matemática Aplicada (CEDEMA), Argentina Facultad de Ingeniería, Universidad de Buenos Aires, Argentina.

Rosa Piotrkowski was born in Lodz, Poland, in 1946 and arrived in Argentina in 1949. In 1971 she obtained a Bachelor's degree in Physical Sciences and in 1990 a PhD in Physical Sciences. Both degrees were obtained in Buenos Aires University, Argentina. She worked between 1978 and 1995 at the National Atomic Energy Commission in experimental studies and codes and models of diffusion in solid materials. Since 1995 she has been teaching and researching in the Departments of Mathematics and Electronics of San Martín National University, in the Faculty of Engineering of Buenos Aires University and in the National Technological University. She was a researcher in the Department of Applied Physics of the University of Granada, Spain. She is currently a member of the Institute of Emerging Technologies and Applied Sciences UNSAM-CONICET and is a consulting associate professor at the Faculty of Engineering of Buenos Aires University, where she dictates a postgraduate course on the analysis of non-stationary and non-linear time series and is the director of a research group. She directs Research Projects and master's and doctoral theses. She published more than 40 articles and book chapters in international journals indexed in the SCOPUS database and her current topics of interest involve modeling and analysis of time series of non-stationary and non-linear stochastic processes.

Pedro David Arini, Instituto Argentino de Matemática "Alberto P. Calderón", CONICET, Ciudad Autónoma de Buenos Aires, Argentina. Instituto de Ingeniería Biomédica, Facultad de Ingeniería, Universidad de Buenos Aires, Argentina.

Pedro David Arini was born in Buenos Aires, Argentina in 1964. In 1995, he obtained the M.S. degree in electronic engineering from the National Technological University, Argentina. Also, he received the M.Sc. degree in biomedical engineering from the Favaloro University of Buenos Aires Argentina in 2001. He subsequently carried out doctoral studies on electrical cardiac signals processing with the aim to evaluate cardiac risk based on biological and mathematical models. He received the PhD degree in biomedical engineering from the Zaragoza University, Spain, in 2007. He worked in several areas, such as video systems, control engineering, acquisition and register of biological signals, speech signal processing, neuroscience, cardiac electrophysiology and digital processing of biomedical signals.
Since 2008, he has been an Independent Research Scientist of the National Council for Scientifics Research and Technical, CONICET, and develops his research work in the Cardio-Signals Research Group at the Argentine Institute of Mathematics “Alberto P. Calderon”. Since 2010, he has been an associate professor of Signals and Images in Biomedicine at the Biomedical Engineering Institute of the Engineering Faculty from the Buenos Aires University, UBA. He published more than 45 scientific articles in international journals and his current research interests include biomedical signal processing, with main interest in signals of cardiovascular origin.

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Published

2022-08-03

How to Cite

Fernández Biscay, C., Bonomini, M. P., Zitto, M. E., Piotrkowski, R., & Arini, P. D. (2022). Cardiac Ischemia Detection Using Parameters Extracted from the Intrinsic Mode Functions. IEEE Latin America Transactions, 20(12), 2439–2447. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/6492

Issue

Vol. 20 No. 12 (2022): Ordinary Issue

Section

Electronics