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Independent Detection of T-Waves in Single Lead ECG Signal Using Continuous Wavelet Transform

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Abstract

Introduction

In the ECG signals, T-waves play a very important role in the detection of cardiac arrest. During myocardial ischemia, the first significant change occurs on the T-wave. These waves are generated due to the repolarization of the heart ventricle. The independent detection of T-waves is a bit challenging due to its variable nature, therefore, most of the algorithms available in the literature for T-wave detection use the detection of the QRS complex as the starting point. But accurate detection of Twave is very much required, as clinically, the first indication of a shortage of blood supply to the heart muscle (myocardial ischemia) shows up as changes in T-wave followed by other changes in the morphology of the ECG signal.

Materials and Methods

In this paper, an efficient and novel algorithm based on Continuous Wavelet Transform (CWT) is presented to detect the Twave independently. In CWT, for better matching, a new mother wavelet is designed using the pattern and shape of the Twave. This algorithm is validated on all the signals of the QT database.

Conclusion

The algorithm attains an average sensitivity of 99.88% and positive predictivity of 99.81% for the signals annotated by the cardiologists in the database.

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Data Availability

The raw data required to reproduce these findings are available to download from pysionet.org.

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Funding

This study was funded by the Government of India, Ministry of Science and Technology, Department of Science and Technology, (Grant number: SR/WOS-A/ET-1049/2015(G)).

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Authors and Affiliations

  1. The NorthCap University, Gurgaon, India

    Pooja Sabherwal

  2. CARE, IIT Delhi, New Delhi, India

    Monika Agrawal

  3. Sushant University, Gurgaon, India

    Latika Singh

Authors
  1. Pooja Sabherwal
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  2. Monika Agrawal
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  3. Latika Singh
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Corresponding author

Correspondence to Pooja Sabherwal.

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Conflict of interest

Pooja Sabherwal has received research grants from the Department of Science and Technology, India. Dr. Latika Singh declares that she has no conflict of interest. Dr. Monika Agrawal declares that she has no conflict of interest.

Ethical Approval

This article does not contain any studies with animals and humans performed by any of the authors. All the analysis of the algorithm has been done on the freely available data from physionet.org.

Additional information

Associate Editor Christian Zemlin oversaw the review of this article.

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Appendix

Appendix

Table 2 Results of QT Database.
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Sabherwal, P., Agrawal, M. & Singh, L. Independent Detection of T-Waves in Single Lead ECG Signal Using Continuous Wavelet Transform. Cardiovasc Eng Tech 14, 167–181 (2023). https://doi.org/10.1007/s13239-022-00643-1

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  • DOI: https://doi.org/10.1007/s13239-022-00643-1

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