Performance of a real-time dicrotic notch detection and prediction algorithm in arrhythmic human aortic pressure signals

Andrea Donelli, Jos R C Jansen, Bas Hoeksel, Paolo Pedeferri, Ramzi Hanania, Jan Bovelander, Francesco Maisano, Alessandro Castiglioni, Ottavio Alfieri, Jan J. Schreuder

Research output: Contribution to journalArticlepeer-review

Abstract

A novel algorithm for real-time detection and prediction of the dicrotic notch from aortic pressure waves was evaluated in arrhythmic aortic pressure signals from heart failure patients. A simplified model of the arterial tree was used to calculate real-time aortic flow from aortic pressure. The dicrotic notch was detected at the first negative dip from the calculated flow, prediction of the notch was performed using a percentage of the decreasing flow. The performance of the real-time dicrotic notch detection algorithm (RTDND) was evaluated during severe arrhythmia from aortic pressure signals of 12 patients. The RTDND was able to detect the dicrotic notch in 98.1%. No false positive dicrotic notch identifications were observed. Prediction of the dicrotic notch was tested at 40%, 20%, and 0% of the decreasing calculated aortic flow. The mean time-delays to the notch were 68 ± 14 ms, 55 ± 12 ms, and 43 ± 8 ms, respectively. Given these small variability, intra-beat prediction of the dicrotic notch may be used for real-time intra-aortic balloon counterpulsation inflation timing.

Original languageEnglish
Pages (from-to)181-185
Number of pages5
JournalJournal of Clinical Monitoring and Computing
Volume17
Issue number3-4
DOIs
Publication statusPublished - 2002

Keywords

  • Dicrotic notch
  • IABP
  • Windkessel model

ASJC Scopus subject areas

  • Anesthesiology and Pain Medicine
  • Health Informatics
  • Health Information Management

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