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Author Notes:

Ikaro Silva: ikaro@mit.edu

Subject:

Research Funding:

This work was funded in part by NIH/NIGMS grant R01 GM104987

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Technology
  • Biophysics
  • Engineering, Biomedical
  • Physiology
  • Engineering
  • ECG
  • blood pressure
  • multimodal
  • beat detection
  • PhysioNet Challenge
  • heart rate
  • data fusion
  • SIGNAL QUALITY INDEXES
  • SOFTWARE QRS DETECTION
  • OPEN-SOURCE ALGORITHM
  • BLOOD-PRESSURE
  • ECG ANALYSIS
  • WAVE-FORMS
  • EXTRACTION
  • FILTER
  • RULES
  • NOISY

Robust detection of heart beats in multimodal data

Tools:

Journal Title:

Physiological Measurement

Volume:

Volume 36, Number 8

Publisher:

, Pages 1629-1644

Type of Work:

Article | Post-print: After Peer Review

Abstract:

This editorial reviews the background issues, the design, the key achievements, and the follow-up research generated as a result of the PhysioNet/Computing in Cardiology (CinC) Challenge 2014, published in the concurrent focus issue of Physiological Measurement. Our major focus was to accelerate the development and facilitate the comparison of robust methods for locating heart beats in long-term multi-channel recordings. A public (training) database consisting of 151 032 annotated beats was compiled from records that contained ECGs as well as pulsatile signals that directly reflect cardiac activity, and other signals that may have few or no observable markers of heart beats. A separate hidden test data set (consisting of 152 478 beats) is permanently stored at PhysioNet, and a public framework has been developed to provide researchers with the ability to continue to automatically score and compare the performance of their algorithms. A scoring criteria based on the averaging of gross sensitivity, gross positive predictivity, average sensitivity, and average positive predictivity is proposed. The top three scores (as of March 2015) on the hidden test data set were 93.64%, 91.50%, and 90.70%.

Copyright information:

© 2015 Institute of Physics and Engineering in Medicine.

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