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Quantitative analysis of QRS detection algorithms based on the first derivative of the ECG.

Publication ,  Journal Article
Arzeno, NM; Poon, C-S; Deng, Z-D
Published in: Conf Proc IEEE Eng Med Biol Soc
2006

Accurate processing of electrocardiogram (ECG) signals requires a sensitive and robust QRS detection method. In this study, three methods are quantitatively compared using a similar algorithm structure but applying different transforms to the differentiated ECG. The three transforms used are the Hilbert transformer, the squaring function, and a second discrete derivative stage. The first two have been widely used in ECG and heart rate variability analysis while the second derivative method aims to explain the success of the Hilbert transform. The algorithms were compared in terms of the number of false positive and false negative detections produced for records of the MIT/BIH Arrhythmia Database. The Hilbert transformer and the squaring function both produced a sensitivity and positive predictivity of over 99%, though the squaring function had a lower overall detection error rate. The second derivative resulted in the highest overall detection error rate. Different algorithms performed better for diverse ECG characteristics; suggesting that an algorithm can be specified for different recordings, the algorithms can be combined based on each one's characteristics to determine a new more accurate method, or an additional detection stage can be added to reduce the number of false negatives.

Duke Scholars

Published In

Conf Proc IEEE Eng Med Biol Soc

DOI

ISSN

1557-170X

Publication Date

2006

Volume

2006

Start / End Page

1788 / 1791

Location

United States

Related Subject Headings

  • Sensitivity and Specificity
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Humans
  • Heart Rate
  • Electrocardiography
  • Diagnosis, Computer-Assisted
  • Artificial Intelligence
  • Arrhythmias, Cardiac
  • Algorithms
 

Citation

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Arzeno, N. M., Poon, C.-S., & Deng, Z.-D. (2006). Quantitative analysis of QRS detection algorithms based on the first derivative of the ECG. Conf Proc IEEE Eng Med Biol Soc, 2006, 1788–1791. https://doi.org/10.1109/IEMBS.2006.260051
Arzeno, Natalia M., Chi-Sang Poon, and Zhi-De Deng. “Quantitative analysis of QRS detection algorithms based on the first derivative of the ECG.Conf Proc IEEE Eng Med Biol Soc 2006 (2006): 1788–91. https://doi.org/10.1109/IEMBS.2006.260051.
Arzeno NM, Poon C-S, Deng Z-D. Quantitative analysis of QRS detection algorithms based on the first derivative of the ECG. Conf Proc IEEE Eng Med Biol Soc. 2006;2006:1788–91.
Arzeno, Natalia M., et al. “Quantitative analysis of QRS detection algorithms based on the first derivative of the ECG.Conf Proc IEEE Eng Med Biol Soc, vol. 2006, 2006, pp. 1788–91. Pubmed, doi:10.1109/IEMBS.2006.260051.
Arzeno NM, Poon C-S, Deng Z-D. Quantitative analysis of QRS detection algorithms based on the first derivative of the ECG. Conf Proc IEEE Eng Med Biol Soc. 2006;2006:1788–1791.

Published In

Conf Proc IEEE Eng Med Biol Soc

DOI

ISSN

1557-170X

Publication Date

2006

Volume

2006

Start / End Page

1788 / 1791

Location

United States

Related Subject Headings

  • Sensitivity and Specificity
  • Reproducibility of Results
  • Pattern Recognition, Automated
  • Humans
  • Heart Rate
  • Electrocardiography
  • Diagnosis, Computer-Assisted
  • Artificial Intelligence
  • Arrhythmias, Cardiac
  • Algorithms