Use of the Kalman Filter for Aortic Pressure Waveform Noise Reduction

Frank Lam, Hsiang Wei Lu, Chung Che Wu, Zekeriya Aliyazicioglu, James S. Kang

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Clinical applications that require extraction and interpretation of physiological signals or waveforms are susceptible to corruption by noise or artifacts. Real-time hemodynamic monitoring systems are important for clinicians to assess the hemodynamic stability of surgical or intensive care patients by interpreting hemodynamic parameters generated by an analysis of aortic blood pressure (ABP) waveform measurements. Since hemodynamic parameter estimation algorithms often detect events and features from measured ABP waveforms to generate hemodynamic parameters, noise and artifacts integrated into ABP waveforms can severely distort the interpretation of hemodynamic parameters by hemodynamic algorithms. In this article, we propose the use of the Kalman filter and the 4-element Windkessel model with static parameters, arterial compliance C, peripheral resistance R, aortic impedance r, and the inertia of blood L, to represent aortic circulation for generating accurate estimations of ABP waveforms through noise and artifact reduction. Results show the Kalman filter could very effectively eliminate noise and generate a good estimation from the noisy ABP waveform based on the past state history. The power spectrum of the measured ABP waveform and the synthesized ABP waveform shows two similar harmonic frequencies.

Original languageEnglish
Article number6975085
JournalComputational and Mathematical Methods in Medicine
Volume2017
DOIs
Publication statusPublished - Jan 1 2017

Fingerprint

Noise Reduction
Blood pressure
Hemodynamics
Noise abatement
Blood Pressure
Kalman filters
Waveform
Kalman Filter
Noise
Arterial Pressure
Artifacts
Critical Care
Power spectrum
Electric Impedance
Vascular Resistance
Parameter estimation
Compliance
Estimation Algorithms
Monitoring System
Power Spectrum

ASJC Scopus subject areas

  • Modelling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Applied Mathematics

Cite this

Use of the Kalman Filter for Aortic Pressure Waveform Noise Reduction. / Lam, Frank; Lu, Hsiang Wei; Wu, Chung Che; Aliyazicioglu, Zekeriya; Kang, James S.

In: Computational and Mathematical Methods in Medicine, Vol. 2017, 6975085, 01.01.2017.

Research output: Contribution to journalArticle

Lam, Frank ; Lu, Hsiang Wei ; Wu, Chung Che ; Aliyazicioglu, Zekeriya ; Kang, James S. / Use of the Kalman Filter for Aortic Pressure Waveform Noise Reduction. In: Computational and Mathematical Methods in Medicine. 2017 ; Vol. 2017.
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