An Adaptive Kalman Filter for Removing Baseline Wandering

Authors

Mohamed A. Mneimneh, Retail Supply NetworkFollow
Edwin E. Yaz, Marquette UniversityFollow
Michael T. Johnson, Marquette UniversityFollow
Richard J. Povinelli, Marquette UniversityFollow

Document Type

Conference Proceeding

Language

eng

Format of Original

4 p.

Publication Date

9-17-2006

Publisher

Institute of Electrical and Electronics Engineers

Source Publication

Computers in Cardiology, 2006

Source ISSN

978-1-4244-2532-7

Abstract

Baseline wandering interference misleads ECG anno- tators 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.

Comments

Accepted version. Published as part of the proceedings of the conference, Computers in Cardiology, 2006: 253-256. Permalink. © 2006 The Institute of Electrical and Electronics Engineers. Used with permission.

Recommended Citation

Mneimneh, Mohamed A.; Yaz, Edwin E.; Johnson, Michael T.; and Povinelli, Richard J., "An Adaptive Kalman Filter for Removing Baseline Wandering" (2006). Electrical and Computer Engineering Faculty Research and Publications. 113.
https://epublications.marquette.edu/electric_fac/113