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Analysis of first-derivative based QRS detection algorithms.

Publication ,  Journal Article
Arzeno, NM; Deng, Z-D; Poon, C-S
Published in: IEEE Trans Biomed Eng
February 2008

Accurate QRS detection is an important first step for the analysis of heart rate variability. Algorithms based on the differentiated ECG are computationally efficient and hence ideal for real-time analysis of large datasets. Here, we analyze traditional first-derivative based squaring function (Hamilton-Tompkins) and Hilbert transform-based methods for QRS detection and their modifications with improved detection thresholds. On a standard ECG dataset, the Hamilton-Tompkins algorithm had the highest detection accuracy (99.68% sensitivity, 99.63% positive predictivity) but also the largest time error. The modified Hamilton-Tompkins algorithm as well as the Hilbert transform-based algorithms had comparable, though slightly lower, accuracy; yet these automated algorithms present an advantage for real-time applications by avoiding human intervention in threshold determination. The high accuracy of the Hilbert transform-based method compared to detection with the second derivative of the ECG is ascribable to its inherently uniform magnitude spectrum. For all algorithms, detection errors occurred mainly in beats with decreased signal slope, such as wide arrhythmic beats or attenuated beats. For best performance, a combination of the squaring function and Hilbert transform-based algorithms can be applied such that differences in detection will point to abnormalities in the signal that can be further analyzed.

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Published In

IEEE Trans Biomed Eng

DOI

EISSN

1558-2531

Publication Date

February 2008

Volume

55

Issue

2 Pt 1

Start / End Page

478 / 484

Location

United States

Related Subject Headings

  • Sensitivity and Specificity
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Humans
  • Electrocardiography
  • Diagnosis, Computer-Assisted
  • Biomedical Engineering
  • Arrhythmias, Cardiac
  • Algorithms
  • 4603 Computer vision and multimedia computation
 

Citation

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Arzeno, N. M., Deng, Z.-D., & Poon, C.-S. (2008). Analysis of first-derivative based QRS detection algorithms. IEEE Trans Biomed Eng, 55(2 Pt 1), 478–484. https://doi.org/10.1109/TBME.2007.912658
Arzeno, Natalia M., Zhi-De Deng, and Chi-Sang Poon. “Analysis of first-derivative based QRS detection algorithms.IEEE Trans Biomed Eng 55, no. 2 Pt 1 (February 2008): 478–84. https://doi.org/10.1109/TBME.2007.912658.
Arzeno NM, Deng Z-D, Poon C-S. Analysis of first-derivative based QRS detection algorithms. IEEE Trans Biomed Eng. 2008 Feb;55(2 Pt 1):478–84.
Arzeno, Natalia M., et al. “Analysis of first-derivative based QRS detection algorithms.IEEE Trans Biomed Eng, vol. 55, no. 2 Pt 1, Feb. 2008, pp. 478–84. Pubmed, doi:10.1109/TBME.2007.912658.
Arzeno NM, Deng Z-D, Poon C-S. Analysis of first-derivative based QRS detection algorithms. IEEE Trans Biomed Eng. 2008 Feb;55(2 Pt 1):478–484.

Published In

IEEE Trans Biomed Eng

DOI

EISSN

1558-2531

Publication Date

February 2008

Volume

55

Issue

2 Pt 1

Start / End Page

478 / 484

Location

United States

Related Subject Headings

  • Sensitivity and Specificity
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Humans
  • Electrocardiography
  • Diagnosis, Computer-Assisted
  • Biomedical Engineering
  • Arrhythmias, Cardiac
  • Algorithms
  • 4603 Computer vision and multimedia computation