Advertisement

Stockwell Transform Based Time-Frequency Analysis of the ECG Features for Assessment of Risk of Left Ventricular Hypertrophy in Hypertension Patients

  • Raghuvendra Pratap Tripathi
  • Ankita Tiwari
  • Sristi Jha
  • Rohini Srivastava
  • Nitin Sahai
  • Sudip Paul
  • Basant Kumar
  • T. K. Sinha
  • Dinesh BhatiaEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 587)

Abstract

Hypertension is a major disease that affects millions of people world-wide. If hypertension remains untreated for long time it could give rise to an enlarged heart condition called Left Ventricular Hypertrophy (LVH). However, recent research in medical domain proposes that left ventricular diastolic dysfunction (LVDD) may be considered as a preceding indicator of LVH. The analysis of ECG signal has shown significant results in identifying LVDD condition that can lead to LVH, however the analysis method till date have remain limited to the manual examination of time domain features of ECG parameters by the experts which is time consuming and cumbersome. Since the time-frequency analysis of the ECG signal have shown more promising results in diagnosis of any abnormality related to the cardiac system, therefore the application of this method is employed in the patients suffering from hypertension and for assessment of the future risk(s) in developing LVH. In the study, we have proposed a Stockwell Transform based time-frequency analysis method of the ECG features (QRS Complex, P-Wave and T-Wave) for accessing the preceding stage of the myocardial remodeling phase. To perform the study, ECG features of the 60 subjects recorded from hospital comprising of 30 controlled and 30 hypertension cases were studied. At the location of the QRS interval a spreading in the power is observed in diseased patients, which signifies increased ventricular activation time, also the power level of the P-Wave and T-Wave have shown significant changes. Increased Ventricular activation time and P-Wave dispersion observed in the frequency domain along with P-wave terminal force, can be used as an indicator of associated risk of developing Left Ventricular Hypertrophy.

Keywords

Left ventricular diastolic dysfunction (LVDD) Left ventricular hypertrophy (LVH) Stockwell transform Time-Frequency analysis 

Notes

Acknowledgements

The authors would like to graciously acknowledge the financial assistance provided by the Department of Biotechnology, Govt. of India vide the grant no. BT/PR15673/NER/95/22/2015 dated 09.12.2016 to the University.

Conflict of Interest There is no conflict of interest associated with publication of this research article.

Ethical Approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Ethics Committee (IEC) of the North Eastern Hill University and North Eastern Indira Gandhi Regional Institute of Health and Medical Sciences, Shillong Meghalaya.

Informed Consent Written consent was informed and obtained from all individual participants included in the study.

References

  1. 1.
    Sowers, James R., Epstein, Murray, Frohlich, Edward D.: Diabetes, hypertension, and cardiovascular disease: an update. Hypertension 37(4), 1053–1059 (2001)CrossRefGoogle Scholar
  2. 2.
    Chockalingam, A., Campbell, N.R., Fodor, J.G.: Worldwide epidemic of hypertension. Can. J. Cardiol. 22(7), 553–555 (2006)CrossRefGoogle Scholar
  3. 3.
    Levy, Daniel: Left ventricular hypertrophy. Drugs 35(5), 1–5 (1988)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Lorell, B.H., Carabello, B.A.: Left ventricular hypertrophy: pathogenesis, detection, and prognosis. Circulation 102(4), 470–479 (2000)CrossRefGoogle Scholar
  5. 5.
    Ishikawa, J., Ishikawa, S., Kabutoya, T., Gotoh, T., Kayaba, K., Schwartz, J.E., Kario, K.: Cornell product left ventricular hypertrophy in electrocardiogram and the risk of stroke in a general population. Hypertension 53(1), 28–34 (2009)CrossRefGoogle Scholar
  6. 6.
    Schröder, J., Nuding, S., Müller-Werdan, U., Werdan, K., Kluttig, A., Russ, M., Medenwald, D.: Performance of Sokolow-Lyon index in detection of echocardiographically diagnosed left ventricular hypertrophy in a normal Eastern German population-results of the CARLA study. BMC Cardiovasc. Disord. 15(1), 69 (2015)Google Scholar
  7. 7.
    Cabezas, M., Comellas, A., Ramón, J.G., López, L.G., Casal, H., Carrillo, N., Castillo, R.: Comparison of the sensitivity and specificity of the electrocardiography criteria for left ventricular hypertrophy according to the methods of Romhilt-Estes, Sokolow-Lyon, Cornell and Rodríguez Padial. Rev. Espanola Cardiol. 50(1), 31–35 (1997)Google Scholar
  8. 8.
    Boles, U., Enriquez, A., Ghabra, W.A., Abdollah, H., Michael, K.A.: Early changes on the electrocardiogram in hypertension E-J. Cardiol. Pract. 13(30) (2015)Google Scholar
  9. 9.
    Tsutsumi, T., Okamoto, Y., Kubota-Takano, N., Wakatsuki, D., Suzuki, H., Sezaki, K., Nakajima, T.: Time–frequency analysis of the QRS complex in patients with is-chemic cardiomyopathy and myocardial infarction. IJC Hear. Vessel. 4, 177–187 (2014)CrossRefGoogle Scholar
  10. 10.
    Biswal, B.: ECG signal analysis using modified S-transform. Healthc. Technol. Lett. 4(2), 68 (2017)CrossRefGoogle Scholar
  11. 11.
    Saritha, C., Sukanya, V., Murthy, Y.N.: ECG signal analysis using wavelet transforms. Bulg. J. Phys. 35(1), 68–77 (2008)zbMATHGoogle Scholar
  12. 12.
    Odinaka, I., Lai, P.H., Kaplan, A.D., O’Sullivan, J.A., Sirevaag, E.J., Kristjansson, S.D., Rohrbaugh, J.W.: ECG biometrics: a robust short-time frequency analysis. In: 2010 IEEE International Workshop on Information Forensics and Security (Wifs), pp 1–6. IEEE (2010)Google Scholar
  13. 13.
    Boashash, B.: Time-Frequency Signal Analysis and Processing: A Comprehensive Reference. Academic Press (2015)Google Scholar
  14. 14.
    Khadra, L., Al-Fahoum, A.S., Binajjaj, S.: A quantitative analysis approach for cardiac arrhythmia classification using higher order spectral techniques. IEEE Trans. Biomed. Eng. 52(11), 1840–1845 (2005)CrossRefGoogle Scholar
  15. 15.
    Gosse, P.: Left ventricular hypertrophy as a predictor of cardiovascular risk. J. Hypertens. 23, S27–S33 (2005)CrossRefGoogle Scholar
  16. 16.
    Wang, Y., Orchard, J.: Fast discrete orthonormal Stockwell transform. SIAM J. Sci. Comput. 31(5), 4000–4012 (2009)MathSciNetCrossRefGoogle Scholar
  17. 17.
    Neubert, S., Arndt, D., Thurow, K., Stoll, R.: Mobile real-time data acquisition system for application in preventive medicine. Telemed. E-Health 16(4), 504–509 (2010)CrossRefGoogle Scholar
  18. 18.
    Bolkhovsky, J.B., Scully, C.G., Chon, K.H.: Statistical analysis of heart rate and heart rate variability monitoring through the use of smart phone cameras. In: 2012 Annual International Conference of the IEEE, Engineering in Medicine and Biology Society (EMBC), pp. 1610–1613. IEEE (2012)Google Scholar
  19. 19.
    Johnson, P., Stemple, C.: Math, art and technology, a cross roads. In: Society for Information Technology and Teacher Education International Conference, pp. 2921–2924. Association for the Advancement of Computing in Education (AACE) (2005)Google Scholar
  20. 20.
    Ieva, F., Paganoni, A.M.: Depth measures for multivariate functional da-ta. Commun. Stat. Theory Methods 42(7), 1265–1276 (2013)CrossRefGoogle Scholar
  21. 21.
    Gosse, P., Jan, E., Coulon, P., Cremer, A., Papaioannou, G., Yeim, S.: ECG detection of left ventricular hypertrophy: the simpler, the better? J. Hypertens. 30(5), 990–996 (2012)CrossRefGoogle Scholar
  22. 22.
    Boles, U., Almuntaser, I., Brown, A., Murphy, R.R., Mahmud, A., Feely, J.: Ventricular activation time as a marker for diastolic dysfunction in early hyperten-sion. Am. J. Hypertens. 23(7), 781–785 (2010)CrossRefGoogle Scholar
  23. 23.
    Equivital, EQ02.: LifeMonitor Sensor Electronic Module Datasheet (2012)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Raghuvendra Pratap Tripathi
    • 1
  • Ankita Tiwari
    • 1
  • Sristi Jha
    • 1
  • Rohini Srivastava
    • 2
  • Nitin Sahai
    • 1
  • Sudip Paul
    • 1
  • Basant Kumar
    • 2
  • T. K. Sinha
    • 1
  • Dinesh Bhatia
    • 1
    Email author
  1. 1.Department of Biomedical EngineeringSchool of Technology, North Eastern Hill UniversityShillongIndia
  2. 2.Department of Biomedical EngineeringSchool of Technology, North Eastern Hill UniversityPrayagrajIndia

Personalised recommendations