Analysis of the Electromechanical Activity of the Heart from Synchronized ECG and PCG Signals of Subjects Under Stress

Ana Castro, Ali Moukadem, Samuel Schmidt, Alain Dieterlen, Miguel T. Coimbra

2015

Abstract

In this exploratory study we propose to analyze, in healthy adult volunteers, the heart electrical (electrocardiogram, ECG) and mechanical (phonocardiogram, PCG) activity during exercise. Heart sounds amplitude, frequency content, and RS2, may be important features in the non-invasive assessment of heart activity, such as for the estimation of cardiac output and blood pressure. Nine healthy volunteers were monitored with ECG and PCG simultaneously, under a stress test. After each workload level a 10 s window of signal was collected. PCG first (S1) and second (S2) heart sounds were manually annotated, based on time of QRS complex occurrence. A QRS detector was implemented to detect the QRS complex, and time intervals between electrical and mechanical events. Extracted features were analyzed in relation to heart rate (HR), including RS2, S1 and S2 amplitudes, and high frequency content of S1 and S2. Spearman correlation was used. Changes between baseline and maximum workload stage/HR for each volunteer were analyzed. Significant correlation was observed between HR, and all characteristics extracted (P<0.01). There was a clear difference between all variables from baseline to maximum workload level: with increasing workload/HR heart sounds amplitude increased (more pronounced in S1), RS2 decreased, and high frequency content of S2 decreased in relation to the high frequency content of S1, demonstrating that dynamic cardiovascular relations are individualized during cardiac stress and that assumptions for resting conditions may not be assumed.

References

  1. Assous, S. and Boashash, B. (2012). Evaluation of the modified s-transform for time-frequency synchrony analysis and source localisation. EURASIP Journal on Advances in Signal Processing, 2012(1).
  2. Bartels, A. and Harder, D. (1992). Non-invasive determination of systolic blood pressure by heart sound pattern analysis. Clinical Physics and Physiological Measurement, 13(3):249 -256.
  3. Biswal, M. and Dash, P. (2013). Detection and characterization of multiple power quality disturbances with a fast s-transform and decision tree based classifier. Digital Signal Processing, 23(4):1071 - 1083.
  4. (2010). Comparison of systolic time interval measurement modalities for portable devices. In Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE, pages 606-609.
  5. Chandrasekaran, V., Dantu, R., Jonnada, S., Thiyagaraja, S., and Subbu, K. (2013). Cuffless differential blood pressure estimation using smart phones. Biomedical Engineering, IEEE Transactions on, 60(4):1080- 1089.
  6. Dennis, A., Michaels, A. D., Arand, P., and Ventura, D. (2010). Noninvasive diagnosis of pulmonary hypertension using heart sound analysis. Computers in Biology and Medicine, 40(9):758 - 764.
  7. Felner, J. M. (1990a). Clinical Methods: The History, Physical, and Laboratory Examinations, chapter 22. The First Heart Sound. CRC Press, Boston: Butterworths.
  8. Felner, J. M. (1990b). Clinical Methods: The History, Physical, and Laboratory Examinations, chapter 23. The Second Heart Sound. CRC Press, Boston: Butterworths.
  9. Guyton, A. and Hall, J. E., editors (2006). Textbook of Medical Physiology. Elsevier Saunders, 11th edition.
  10. Hansen, J., Zimmermann, H., Schmidt, S., Hammershoi, D., and Struijk, J. (2011). System for acquisition of weak murmurs related to coronary artery diseases. In Computing in Cardiology, 2011, pages 213-216.
  11. Kohler, B.-U., Hennig, C., and Orglmeister, R. (2002). The principles of software qrs detection. Engineering in Medicine and Biology Magazine, IEEE, 21(1):42-57.
  12. Moukadem, A., Dieterlen, A., Hueber, N., and Brandt, C. (2013). A robust heart sounds segmentation module based on s-transform. Biomedical Signal Processing and Control, 8(3):273 - 281.
  13. Paiva, R., Carvalho, P., Aubert, X., Muehlsteff, J., Henriques, J., and Antunes, M. (2009). Assessing pep and lvet from heart sounds: Algorithms and evaluation. In Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE, pages 3129-3133.
  14. Pinnegar, C. R. and Mansinha, L. (2003). The s-transform with windows of arbitrary and varying shape. Geophysics, 68(1):381-385.
  15. Pluim, B. M., Zwinderman, A. H., van der Laarse, A., and van der Wall, E. E. (2000). The athletes heart: A metaanalysis of cardiac structure and function. Circulation, 101(3):336-344.
  16. Ronved, S., Gjerlov, I., Brokjaer, A., and Schmidt, S. (2011). Phonocardiographic recordings of first and second heart sound in determining the systole/diastole-ratio during exercise test. In Dremstrup, K., Rees, S., and Jensen, M., editors, 15th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC 2011), volume 34 of IFMBE Proceedings, pages 85-88. Springer Berlin Heidelberg.
  17. Smith, R. and Ventura, D. (2013). A general model for continuous noninvasive pulmonary artery pressure estimation. Computers in Biology and Medicine, 43(7):904 - 913.
  18. Sola, J., Chetelat, O., Sartori, C., Allemann, Y., and Rimoldi, S. (2011). Chest pulse-wave velocity: A novel approach to assess arterial stiffness. Biomedical Engineering, IEEE Transactions on, 58(1):215-223.
  19. Sola, J., Proenca, M., Ferrario, D., Porchet, J.-A., Falhi, A., Grossenbacher, O., Allemann, Y., Rimoldi, S., and Sartori, C. (2013). Noninvasive and nonocclusive blood pressure estimation via a chest sensor. Biomedical Engineering, IEEE Transactions on, 60(12):3505- 3513.
  20. Stockwell, R. G., Mansinha, L., and Lowe, R. P. (1996). Localization of the complex spectrum: the s transform. Signal Processing, IEEE Transactions on, 44(4):998- 1001.
  21. Sullivan, M. J., Knight, J. D., B., H. M., and Cobb, F. R. (1989). Relation between central and peripheral hemodynamics during exercise in patients with chronic heart failure. muscle blood flow is reduced with maintenance of arterial perfusion pressure. Circulation, 80:769-781.
  22. Xu, J., Durand, L.-G., and Pibarot, P. (2001). Extraction of the aortic and pulmonary components of the second heart sound using a nonlinear transient chirp signal model. Biomedical Engineering, IEEE Transactions on, 48(3):277 -283.
  23. Zhang, X.-Y., MacPherson, E., and Zhang, Y.-T. (2008). Relations between the timing of the second heart sound and aortic blood pressure. Biomedical Engineering, IEEE Transactions on, 55(4):1291 -1297.
  24. Zheng, Y.-L., Ding, X.-R., Poon, C., Lo, B., Zhang, H., Zhou, X.-L., Yang, G.-Z., Zhao, N., and Zhang, Y.- T. (2014). Unobtrusive sensing and wearable devices for health informatics. Biomedical Engineering, IEEE Transactions on, 61(5):1538-1554.
  25. Zidelmal, Z., Amirou, A., Adnane, M., and Belouchrani, A. (2012). Qrs detection based on wavelet coefficients. Computer Methods and Programs in Biomedicine, 107(3):490 - 496.
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Paper Citation


in Harvard Style

Castro A., Moukadem A., Schmidt S., Dieterlen A. and T. Coimbra M. (2015). Analysis of the Electromechanical Activity of the Heart from Synchronized ECG and PCG Signals of Subjects Under Stress . In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015) ISBN 978-989-758-069-7, pages 49-56. DOI: 10.5220/0005202400490056


in Bibtex Style

@conference{biosignals15,
author={Ana Castro and Ali Moukadem and Samuel Schmidt and Alain Dieterlen and Miguel T. Coimbra},
title={Analysis of the Electromechanical Activity of the Heart from Synchronized ECG and PCG Signals of Subjects Under Stress},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)},
year={2015},
pages={49-56},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005202400490056},
isbn={978-989-758-069-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2015)
TI - Analysis of the Electromechanical Activity of the Heart from Synchronized ECG and PCG Signals of Subjects Under Stress
SN - 978-989-758-069-7
AU - Castro A.
AU - Moukadem A.
AU - Schmidt S.
AU - Dieterlen A.
AU - T. Coimbra M.
PY - 2015
SP - 49
EP - 56
DO - 10.5220/0005202400490056