Autonomous Cardiac Diagnostic based on Synchronized ECG and PCG Signal

Z. Bouguila, A. Moukadem, A. Dieterlen, A. Ahmed Benyahia, A. Hajjam, S. Talha, E. Andres

2014

Abstract

Despite considerable advances in medical therapy, heart failure remains a substantial burden of mortality and economic cost. This is tangibly seen by the rising number of healthcare systems that are adopting telemedicine, by the development of industry investments in telemedicine products and involvement of government in project delivery. The main objective of the telemedicine E-care (www.projet-e-care.fr) project is to greatly contribute to the enhancement of the remote patient monitoring, expanding the possibilities for lifesaving care. In this project, oriented for heart failure patients with NYHA (class III) severity, a smart platform is adopted for home monitoring using noninvasive standard sensors and specific cardiac devices (ElectroCardioGram and PhonoCardioGram). This thesis contribution, with our partners, is to enhance the signal processing part for accurate diagnostic. Although ECG and PCG signals play important roles in heart abnormality detection, diagnosis based on this signal individually cannot detect most cases of heart symptoms, like detection of S4 pathological heart sound. Previously in our laboratory, time-frequency methods showed here potential on PCG segmentation and classification; however these methods can suffer from poor energy concentration in time frequency domain. Hence the first theoretical thesis objective is to optimize the energy concentration of Stockwell time-frequency transform. The second objective, based on the first results, is to combine by time-frequency correlation the information contained in PCG and ECG. This original approach will help us extracting features to classify accurately heart disease. All these methods should be validated by an experimented cardiologist during a measure campaign in Strasbourg University Hospital.

References

  1. Ahlstrom, C., Lanne, T., Ask, P. & Johansson, A. 2008. A Method For Accurate Localization Of The First Heart Sound And Possible Applications. Physiol Meas, 29, 417-28.
  2. Assous, S. & Boashash, B. 2012. Evaluation Of The Modified S-Transform For Time-Frequency Synchrony Analysis And Source Localisation. Eurasip J Adv Signal Process, 2012, 49.
  3. Auger, F. & Flandrin, P. 1995. Improving The Readability Of Time-Frequency And Time-Scale Representations By The Reassignment Method. Signal Processing, Ieee Transactions On, 43, 1068-1089.
  4. Auger, F., Flandrin, P., Yu-Ting, L., Mclaughlin, S., Meignen, S., Oberlin, T. & Hau-Tieng, W. 2013. Time-Frequency Reassignment And Synchrosqueezing: An Overview. Signal Processing Magazine, Ieee, 30, 32-41.
  5. Daubechies, I. 1990. The Wavelet Transform, TimeFrequency Localization And Signal Analysis. Information Theory, Ieee Transactions On, 36, 961- 1005.
  6. Daubechies, I. & Maes, S. 1996. A Nonlinear Squeezing Of The Continuous Wavelet Transform Based On Auditory Nerve Models. Wavelets In Medicine And Biology, Crc Press, 527-546.
  7. Djurovic, I., Sejdic, E. & Jiang, J. 2008. Frequency-Based Window Width Optimization For -Transform. Aeu - International Journal Of Electronics And Communications, 62, 245-250.
  8. Dugnol, B., Fernández, C., Galiano, G. & Velasco, J. 2007. Implementation Of A Diffusive Differential Reassignment Method For Signal Enhancement: An Application To Wolf Population Counting. Applied Mathematics And Computation, 193, 374-384.
  9. Erikson, B. 1997. Heart Sounds And Murmurs: A Practical Guide.
  10. European.Commission 2012. Ehealth Action Plan 2012- 2020- Innovative Healthcare For The 21st Century. Brussels.
  11. Fulop, S. A. & Fitz, K. 2006. Algorithms For Computing The Time-Corrected Instantaneous Frequency (Reassigned) Spectrogram, With Applications. J Acoust Soc Am, 119, 360-71.
  12. Jabloun, M., Ravier, P., Buttelli, O., Ledee, R., Harba, R. & Nguyen, L. D. 2013. A Generating Model Of Realistic Synthetic Heart Sounds For Performance Assessment Of Phonocardiogram Processing Algorithms. Biomedical Signal Processing And Control, 8, 455-465.
  13. Kotte, O., Niethammer, M. & Jacobs, L. J. 2006. Lamb Wave Characterization By Differential Reassignment And Non-Linear Anisotropic Diffusion. Ndt & E International, 39, 96-105.
  14. Mansinha, L., Stockwell, R. G. & Lowe, R. P. 1997. Pattern Analysis With Two-Dimensional Spectral Localisation: Applications Of Two-Dimensional S Transforms. Physica A: Statistical Mechanics And Its Applications, 239, 286-295.
  15. Moukadem, A. 2011. Segmentation Et Classification Des Signaux Non-Stationnaires : Application Au Traitement Des Sons Cardiaque Et A L'aide Au Diagnostic. Université De Haute Alsace - Mulhouse.
  16. Moukadem, A., Dieterlen, A., Hueber, N. & Brandt, C. 2013. A Robust Heart Sounds Segmentation Module Based On S-Transform. Biomedical Signal Processing And Control, 8, 273-281.
  17. Phanphaisarn, W., Roeksabutr, A., Wardkein, P., Koseeyaporn, J. & Yupapin, P. 2011. Heart Detection And Diagnosis Based On Ecg And Epcg Relationships. Med Devices (Auckl), 4, 133-44.
  18. Ping, Z. & Zhigang, W. A Computer Location Algorithm For Ecg, Pcg And Cap. Engineering In Medicine And Biology Society, 1998. Proceedings Of The 20th Annual International Conference Of The Ieee, 29 Oct1 Nov 1998 1998. 220-222 Vol.1.
  19. Sejdic, E., Djurovic, I. & Jin, J. S-Transform With Frequency Dependent Kaiser Window. Acoustics, Speech And Signal Processing, 2007. Icassp 2007. Ieee International Conference On, 15-20 April 2007 2007. Iii-1165-Iii-1168.
  20. Sejdic, E. & Jin, J. 2007. Selective Regional Correlation For Pattern Recognition. Systems, Man And Cybernetics, Part A: Systems And Humans, Ieee Transactions On, 37, 82-93.
  21. Stankovic, L. 2001. A Measure Of Some Time-Frequency Distributions Concentration. Signal Processing, 81, 621-631.
  22. Stockwel, R. 2007. Why Use The S-Transform. Ed. By A Wong (Fields Institute Communications, Providence), Pseudo-Differential Operators: Pdes And TimeFrequency Analysis, 279-309.
  23. Stockwell, R. G., Mansinha, L. & Lowe, R. P. 1996. Localization Of The Complex Spectrum: The S Transform. Signal Processing, Ieee Transactions On, 44, 998-1001.
  24. Zannad, F., Agrinier, N. & Alla, F. 2009. Heart Failure Burden And Therapy. Europace, 11 Suppl 5, V1-9.
Download


Paper Citation


in Harvard Style

Bouguila Z., Moukadem A., Dieterlen A., Ahmed Benyahia A., Hajjam A., Talha S. and Andres E. (2014). Autonomous Cardiac Diagnostic based on Synchronized ECG and PCG Signal . In Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2014) ISBN Not Available, pages 36-40


in Bibtex Style

@conference{dcbiostec14,
author={Z. Bouguila and A. Moukadem and A. Dieterlen and A. Ahmed Benyahia and A. Hajjam and S. Talha and E. Andres},
title={Autonomous Cardiac Diagnostic based on Synchronized ECG and PCG Signal},
booktitle={Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2014)},
year={2014},
pages={36-40},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={Not Available},
}


in EndNote Style

TY - CONF
JO - Doctoral Consortium - DCBIOSTEC, (BIOSTEC 2014)
TI - Autonomous Cardiac Diagnostic based on Synchronized ECG and PCG Signal
SN - Not Available
AU - Bouguila Z.
AU - Moukadem A.
AU - Dieterlen A.
AU - Ahmed Benyahia A.
AU - Hajjam A.
AU - Talha S.
AU - Andres E.
PY - 2014
SP - 36
EP - 40
DO -