Model-Based Detection of Heart Rate Turbulence Using Mean Shape Information

Research output: Contribution to journalArticle

Abstract

A generalized likelihood ratio test (GLRT) statistic is proposed for detection of heart rate turbulence (HRT), where a set of Karhunen-Loeve basis functions models HRT. The detector structure is based on the extended integral pulse frequency modulation model that accounts for the presence of ectopic beats and HRT. This new test statistic takes a priori information regarding HRT shape into account, whereas our previously presented GLRT detector relied solely on the energy contained in the signal subspace. The spectral relationship between heart rate variability (HRV) and HRT is investigated for the purpose of modeling HRV "noise" present during the turbulence period, the results suggesting that the white noise assumption is feasible to pursue. The performance was studied for both simulated and real data, leading to results which show that the new GLRT detector is superior to the original one as well as to the commonly used parameter turbulence slope (TS) on both types of data. Averaging ten ventricular ectopic beats, the estimated detection probability of the new detector, the previous detector, and TS were found to be 0.83, 0.35, and 0.41, respectively, when the false alarm probability was held fixed at 0.1.

Details

Authors
  • Danny Smith
  • Kristian Solem
  • Pablo Laguna
  • Juan Pablo Martinez
  • Leif Sörnmo
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Medical Engineering

Keywords

  • Karhunen-Loeve, basis functions, integral pulse frequency modulation (IPFM) model, (HRT), heart rate turbulence, ECG, generalized likelihood ratio test (GLRT)
Original languageEnglish
Pages (from-to)334-342
JournalIEEE Transactions on Biomedical Engineering
Volume57
Issue number2
Publication statusPublished - 2010
Publication categoryResearch
Peer-reviewedYes