Heart Rate Turbulence Detection Using Mean Shape Information

Danny Smith, Kristian Solem, P. Laguna, J. P. Martinez, Leif Sörnmo

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review


In this study, we propose a generalized likelihood ratio test statistic for detection of heart rate turbulence (HRT) based on a linear signal model. The new test statistic, which expands our previous original detector; takes a priori information regarding HRT shape into account. The detector structure is based on the extended integral pulse frequency modulation model which accounts for the presence of ectopic beats and HRT 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 performance was studied for both simulated data and real data obtained from the Long-Term ST database. The results show that the new detector is superior to the original one as well as to the commonly used parameter turbulence slope (TS) on both types of data.
Original languageEnglish
Title of host publicationCINC: 2009 36th Annual Computers in Cardiology Conference
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Publication statusPublished - 2009
Event36th Annual Computers in Cardiology Conference, 2009 - Pk City, UT, Park City, UT, United States
Duration: 2009 Sept 132009 Sept 16
Conference number: 36

Publication series

ISSN (Print)0276-6574


Conference36th Annual Computers in Cardiology Conference, 2009
Abbreviated titleCinC 2009
Country/TerritoryUnited States
CityPark City, UT

Subject classification (UKÄ)

  • Electrical Engineering, Electronic Engineering, Information Engineering


Dive into the research topics of 'Heart Rate Turbulence Detection Using Mean Shape Information'. Together they form a unique fingerprint.

Cite this