An adaptive kalman filter for removing baseline wandering in ECG

Mohamed A. Mneimneh, E. E. Yaz, M. T. Johnson, R. J. Povinelli

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

69 Scopus citations

Abstract

Baseline wandering interference misleads ECG annotators from accurate identification of the ECG features. Previous work that deals with baseline wandering removal requires the identification of the QRS complex or other ECG features prior to baseline removal. This paper proposes an adaptive Kalman filter for the real time removal of baseline wandering using a polynomial approximation independent of the signal characteristics. A state space model is used with an adaptive Kalman filter to estimate the state variables, including the baseline wandering approximation from the previous values of the original ECG signal. This approach is applied to the (PTB) Diagnostic ECG Database and to a ECG signal disturbed by white noise and a second order baseline wandering. The results show accurate and improved baseline wandering estimation and removal as compared to moving averaging and cubic spline techniques.

Original languageEnglish
Title of host publication2006 Computers in Cardiology, CIC
Pages253-256
Number of pages4
StatePublished - 2006
Event2006 Computers in Cardiology, CIC - Valencia, Spain
Duration: Sep 17 2006Sep 20 2006

Publication series

NameComputers in Cardiology
Volume33
ISSN (Print)0276-6574

Conference

Conference2006 Computers in Cardiology, CIC
Country/TerritorySpain
CityValencia
Period9/17/069/20/06

ASJC Scopus subject areas

  • Computer Science Applications
  • Cardiology and Cardiovascular Medicine

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