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Three methods for determining the respiratory waves from ECG (Part II)

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Języki publikacji
EN
Abstrakty
EN
This paper presents the results of a study of three methods for estimating the respiratory wave (RW) and respiratory rate (RR) using the electrocardiogram (ECG). There were applied methods from different groups: amplitude modulation ECG-Derived Respiration (EDR), frequency modulation Respiratory Sinus Arrhythmia (RSA) and Baseline Wander (BW) processing with the Savitzky-Golay filter (S-G). The theoretical aspects of the methods were presented in the Part 1 of the publication which was entitled: “Three Methods for the Determination of the Respiratory Waves from ECG Part I”. RR parameter estimation was performed for all the three methods for 12 subjects. The research concerning the influence of the parameters: Body Mass Index (BMI), Tidal Volume (TV) -, Forced Expiratory Volume in 1 second (FEV1) and - Forced Vital Capacity (FVC) on the errors of the estimated parameter RR. Moreover, all 12 signals, which were acquired with the help of a 12-lead Holter ECG were taken into consideration. The results indicate a preliminary dependence of respiratory parameters and BMI on the Respiratory Wave and, further, on the RR estimation errors. Consequently, the type of method and ECG Holter leads depend on the BMI and respiratory parameters. Studies with larger numbers of objects to definitively confirm these relationships are planned. In addition, an optimal selection of S-G filter parameters was carried out. Finally, a proprietary reference embedded system for recording RW and calculating RR was demonstrated.
Rocznik
Strony
51--71
Opis fizyczny
Bibliogr. 31 poz., rys., tab., wykr.
Twórcy
  • Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76 Street, 45-758 Opole, Poland
  • Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Prószkowska 76 Street, 45-758 Opole, Poland
autor
  • Faculty of Physical Education and Physiotherapy, Opole University of Technology, Prószkowska 76 Street, 45-758 Opole; Department of Cardiology, University Hospital in Opole, 45-401 Opole, Poland
  • Faculty of Electronics, Photonics and Microsystems, Department of Electronic and Photonic Metrology, Wrocław University of Science and Technology, B. Prusa 53/55 Street, 50-317 Wrocław, Poland
Bibliografia
  • [1] Moody, G. B., Mark, R. G., Zocola, A., & Mantero, S. (1985). Derivation of Respiratory Signals from Multi-Lead Ecgs. Computers in Cardiology, 12, 113-116.
  • [2] Moody, G. B., Mark, R. G., Bump, M. A., Weinstein, J. S., Berman, A. D., Mietus, J. E., & Goldberger, A. L. (1987). Clinical Validation of the ECG-Derived Respiration (EDR) Technique. Computers in Cardiology, 13, 507-510.
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  • [4] Tsai, N. C., & Lee, R. M. (2011). Interaction between cardiovascular system and respiration. Applied Mathematical Modelling, 35(11), 5460-5469. https://doi.org/10.1016/j.apm.2011.04.033
  • [5] Cheifetz, I. M. (2014). Cardiorespiratory interactions: The relationship between mechanical ventilation and hemodynamics. Respiratory Care, 59(12), 1937-1945. https://doi.org/10.4187/respcare.03486
  • [6] Nitkiewicz, S., Barański, R., Galewski, M. A., Zajączkiewicz, H., Kukwa, A., Zając, A., Ejdys, S., & Artiemjew, P. (2021). Requirements for supporting diagnostic equipment of respiration process in humans. Sensors, 21(10), 3479. https://doi.org/10.3390/s21103479
  • [7] Zając, A., Kukwa, A., Barański, R., Nitkiewicz, S., Zomkowska, E., & Rybak, A. (2022). Anatomical and Functional Assessment of Patency of the Upper Respiratory Tract in Selected Respiratory Disorders - Part 2. Metrology and Measurement Systems, 29(3), 429-454. https://doi.org/10.24425/mms.2022.142273
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  • [9] Slama, A. B., Lentka, Ł., Mouelhi, A., Diouani, M. F., Sayadi, M., & Smulko, J. (2018). Application of statistical features and multilayer neural network to automatic diagnosis of arrhythmia by ECG signals. Metrology and Measurement Systems, 25(1), 87-101. https://doi.org/10.24425/118163
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  • [11] Polak, A. G., Wysoczański, D., & Mroczka, J. (2006). A multi-method approach to measurement of respiratory system mechanics. Metrology and Measurement Systems, 13(1), 3-17.
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  • [17] Peralta, G. P., Marcon, A., Carsin, A. E., Abramson, M. J., Accordini, S., Amaral, A. F. S., . . . Garcia-Aymerich, J. (2020). Body mass index and weight change are associated with adult lung function trajectories: The prospective ECRHS study. Thorax, 75(4), 313-320. https://doi.org/10.1136/thoraxjnl-2019-213880
  • [18] Natarajan, A., Su, H. W., Heneghan, C., Blunt, L., O’Connor, C., & Niehaus, L. (2021). Measurement of respiratory rate using wearable devices and applications to COVID-19 detection. npj Digital Medicine, 4(1). https://doi.org/10.1038/s41746-021-00493-6
  • [19] Szmajda, M., Chyliński, M., Sacha, J., & Mroczka, J. (2023). Three Methods for Determining the Respiratory Waves from ECG (Part I). Metrology and Measurement Systems, 30(4), 821-837. https://doi.org/10.24425/mms.2023.147956
  • [20] Feher, J. (2012). Quantitative Human Physiology. Academic Press. https://doi.org/10.1016/C2009-0-64018-6
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  • [23] Gold, W. M., & Koth, L. L. (n.d.). 25 - Pulmonary Function Testing. Murray and Nadel’s Text-book of Respiratory Medicine, 2-Volume Set (6th ed.). Elsevier Inc. https://doi.org/10.1016/B978-1-4557-3383-5.00025-7
  • [24] Chyliński, M., Szmajda, M., Sacha, J., & Mroczka, J. (2021, November). The way of ECG signal obtaining from the respiratory wave by Savitzky-Golay filtration. 2021 6th International Conference on Nanotechnology for Instrumentation and Measurement (NanofIM), (pp. 1-4). IEEE. https://doi.org/10.1109/NanofIM54124.2021.9737356
  • [25] Chyliński, M., & Szmajda, M. (2019). Design and Implementation of an Embedded System for Respiratory Rate Examinations. IFAC-PapersOnLine. https://doi.org/10.1016/j.ifacol.2019.12.684
  • [26] NHANES. (2008). Respiratory Health Spirometry Procedures Manual. National Health and Nutrition Examination Survey, 1(January), 1-10.
  • [27] Williamson, D. F., Parker, R. A., & Kendrick, J. S. (1989). The box plot: a simple visual method to interpret data. Annals of Internal Medicine, 110(11), 916-921. https://doi.org/10.7326/0003-4819-110-11-916
  • [28] Chinomso, E., Yusuf, M. F., Umar, S. D., & Mundi, I. (2022). Analysis of Savitzky-Golay Filter for Electrocardiogram De-Noising Using Daubechies Wavelets. EDUCATUM Journal of Science, Mathematics and Technology, 9(2), 113. https://doi.org/10.37134/ejsmt.vol9.2.13.2022
  • [29] Riffenburgh, R. H., & Gillen, D. L. (2020). Statistics in Medicine. Academic Press. https://doi.org/10.1016/b978-0-12-815328-4.00027-9
  • [30] Giavarina, D. (2015). Understanding Bland Altman analysis. Biochemia Medica, 25(2), 141-151. https://doi.org/10.11613/BM.2015.015
  • [31] Doğan, N. Ö. (2018). Bland-Altman analysis: A paradigm to understand correlation and agreement. Turkish Journal of Emergency Medicine, 18(4), 139-141. https://doi.org/10.1016/j.tjem.2018.09.001
Uwagi
The authors acknowledge the support that they have received from the Opole University of Technology for using the Holter ECG. The study was conducted in accordance with Resolution No. 319 of October 1, 2020 of the Bioethics Committee authorizing the conduct of a medical experiment for implementation.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-1e6b3a10-4a6f-47d9-b775-c5eccfb57644
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