Automatic detection of heart diseases based on ECG signal analysis

• Autorzy: Delarue Louis , Drouard Pierre-Amaud , Hourdé Pierre , Joulia Jean , Renault Victorieu , Kotas Rafał
• Języki publikacji: EN

Abstrakty

EN

The authors provide overview of techniques used in ECG signal analysis and present their implementation in order to detect heart diseases (arrhythmias). This paper presents different means to study the ECG signals to develop automatic detection of heart diseases based on artificial intelligence.

Słowa kluczowe

EN

ECG; QRS complex; Pan-Tompkins algorithm; arrhythmia; HRV; heart rate variability; HRT; heart rate turbulence

PL

analiza EKG; zespół QRS; algorytm Pana-Tompkinsa; arytmia; HRV; zmienność rytmu zatokowego; HRT; turbulencja rytmu serca

• Wydawca: Lodz University of Technology. Department of Microelectronics and Computer Science
• Czasopismo: International Journal of Microelectronics and Computer Science
• Rocznik: 2018
• Tom: Vol. 9, nr 4
• Strony: 133--141
• Opis fizyczny: Bibliogr. 11 poz., rys. (w tym kolor.), wykr.

Twórcy

autor

Delarue Louis

• ISEN Lille Engineering School, 41 boulevard Vauban, 59046 Lille Cedex, France

autor

Drouard Pierre-Amaud

• ISEN Lille Engineering School, 41 boulevard Vauban, 59046 Lille Cedex, France

autor

Hourdé Pierre

• ISEN Lille Engineering School, 41 boulevard Vauban, 59046 Lille Cedex, France

autor

Joulia Jean

• ISEN Lille Engineering School, 41 boulevard Vauban, 59046 Lille Cedex, France

autor

Renault Victorieu

• ISEN Lille Engineering School, 41 boulevard Vauban, 59046 Lille Cedex, France

autor

Kotas Rafał

• Department of Microelectronics and Computer Science, Lodz University of Technology, ul. Wólczańska 221/223, 90-924 Lodz. Poland

Bibliografia

• [1] Mendis S, Puska P, Norrving. (Eds.) B, Global Atlas on Cardiovascular Disease Prevention and Control, WHO, Geneva, 2011
• [2] Goldberger AL, Amaral LAN, Glass L. Hausdorff JM, Ivanov PCh, Ivanov PCh, Mark RG, Miętus JE, Moody GB, Peng C-K, Staniey HE. PhysioBank, Physio Toolkit and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals Circulation 101(23): e215-e220
• [3] Pan J, Tompkins WJ, A real-time QRS detection algorithm. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING. VOL. BME-32, NO. 3, MARCH 1985
• [4] Buendia-Fuentes F, Amau-Vives MA, Amau-Vives A, et al. High-Bandpass Fitters in Electrocardiography: Source of Error in the Interpretation of the ST Segment. ISRN Cardiol. 2012;2012:706217
• [5] Elgendi M, Eskofier B, Abbott D (2015) Fast T Wave Detection Calibrated by Clinical Knowledge with Annotation of P and T Waves. Sensors 15(7): 17693-17714
• [6] Sun Y-X, Gao J, Jiang C-Y, Xue Y-M, Xu Y-Z, Liu G, Guo J-H, Sheng X, Ye Y, He H, Zhao Y-T, Barajas-Martinez H, Fu G-S and Hu D (2017) T Wave Safety Margin during the Process of ICD Implantation As a Novel Predictor of T Wave Oversensing. Front. Physiol. 8:659. doi: 10.3389/fphys-2017.00659
• [7] Elgendi M, Eskofier B, Abbott D. Fast T Wave Detection Calibrated by Clinical Knowledge with Annotation of P and T Waves Sensors (Basel). 2015;15(7): 17693-714. Published 2015 Jul 21. doi: 10.3390/s150717693
• [8] Kotas Rafał, Kamiński Marek, Mazur Piotr, Chłapiński Jakub, Sakowicz Bartosz, Napieralski Andrzej, Kurpesa Małgorzata: Project of open-source software platform for sudden cardiac death (SCD) risk stratification and advanced ECG analysis. Przegląd Elektrotechniczny, 2013, rocznik 89, nr 2A, s. 64-67
• [9] Bauer. A., Kantelhardt. J.W., Barthel, P . Schneider. R, Mäkikallio, T.H., Ulm, К., Hnatkova, К., Schoemig, А., Huikuri, Н., Bunde, A., Malik, M., & Schmidt, G. (2006). Deceleration capacity of heart rate as a predictor of mortality after myocardial infarction: cohort study. The Lancet 367, 1674-1681.
• [10] https://physionet.org physiobank/database/mitdb (MIT-BIH database)
• [11] https://www physionet.org/pn3/incartdb (Incart database)

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).