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Novel T-wave Detection Technique with Minimal Processing and RR-Interval Based Enhanced Efficiency

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Cardiovascular Engineering and Technology Aims and scope Submit manuscript

Abstract

Purpose

T-wave in electrocardiogram (ECG) is a vital wave component and has potential of diagnosing various cardiac disorders. The present work proposes a novel technique for T-wave peak detection using minimal pre-processing and simple root mean square based decision rule.

Methods

The technique uses a two-stage median filter and a Savitzky–Golay smoothing filter for pre-processing. P-QRS-complex is removed from the filtered ECG, and T-wave is left as the most prominent wave segment, which can be detected using a root mean square based adaptive threshold. An RR-interval based T-wave peak correction strategy has been proposed which can handle the challenges of morphological variations in the T-wave, thus increases the detection accuracy.

Results

The proposed technique has been substantiated on a standard QT-database. The detection sensitivity = 97.01%, positive predictivity = 99.61%, detection error rate = 3.36%, and accuracy = 96.66% have been achieved.

Conclusions

A T-wave detection technique requiring minimal pre-processing and with simple decision rule has been designed. The noticeably high positive predictivity rate of the proposed technique shows its efficiency to detect T-wave peak.

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Acknowledgments

Authors are thankful to the Ministry of Human Resource Development, Government of India for providing the financial assistance. This work has been done at Medical Imaging and Computational Modeling of Physiological System Research Laboratory at Department of Electronics and Communication Engineering of Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, India.

Conflict of interest

Authors declare that they have no conflict of interest.

Human Studies/Informed Consent

This work uses freely available standard QT-Database for validation of the proposed technique. No human studies were carried out by the authors for this article.

Research Involving Animal Rights

No animal studies were carried out by the authors for this article.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, 144011, India

    Lakhan Dev Sharma & Ramesh Kumar Sunkaria

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  1. Lakhan Dev Sharma
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  2. Ramesh Kumar Sunkaria
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Correspondence to Lakhan Dev Sharma.

Additional information

Associate Editor Ajit P. Yoganathan oversaw the review of this article.

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Sharma, L.D., Sunkaria, R.K. Novel T-wave Detection Technique with Minimal Processing and RR-Interval Based Enhanced Efficiency. Cardiovasc Eng Tech 10, 367–379 (2019). https://doi.org/10.1007/s13239-019-00415-4

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