Improved ECG pre-processing for beat-to-beat QT interval variability measurement

Muhammad A. Hasan, Vito Starc, Alberto Porta, Derek Abbott, Mathias Baumert

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The aim of this study was to enhance the ECG pre-processing modalities for beat-to-beat QT interval variability measurement based on template matching. The R-peak detection algorithm has been substituted and an efficient baseline removal algorithm has been implemented in existing computer software. To test performance we used simulated ECG data with fixed QT intervals featuring Gaussian noise, baseline wander and amplitude modulation and two alternative algorithms. We computed the standard deviation of beat-to-beat QT intervals as a marker of QT interval variability (QTV). Significantly a lower beat-to-beat QTV was found in the updated approach compared the original algorithm. In addition, the updated template matching computer software outperformed the previous version in discarding fewer beats. In conclusion, the updated ECG preprocessing algorithm is recommended for more accurate quantification of beat-to-beat QT interval variability.

Original languageEnglish
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages2563-2566
Number of pages4
DOIs
Publication statusPublished - 2013
Event2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan
Duration: Jul 3 2013Jul 7 2013

Other

Other2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
CountryJapan
CityOsaka
Period7/3/137/7/13

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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