Baseline wander correction in pulse waveforms using wavelet-based cascaded adaptive filter

Lisheng Xu, Dapeng Zhang, Kuanquan Wang, Naimin Li, Xiaoyun Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

75 Citations (Scopus)

Abstract

Pulse diagnosis is a convenient, inexpensive, painless, and non-invasive diagnosis method. Quantifying pulse diagnosis is to acquire and record pulse waveforms by a set of sensor firstly, and then analyze these pulse waveforms. However, respiration and artifact motion during pulse waveform acquisition can introduce baseline wander. It is necessary, therefore, to remove the pulse waveform's baseline wander in order to perform accurate pulse waveform analysis. This paper presents a wavelet-based cascaded adaptive filter (CAF) to remove the baseline wander of pulse waveform. To evaluate the level of baseline wander, we introduce a criterion: energy ratio (ER) of pulse waveform to its baseline wander. If the ER is more than a given threshold, the baseline wander can be removed only by cubic spline estimation; otherwise it must be filtered by, in sequence, discrete Meyer wavelet filter and the cubic spline estimation. Compared with traditional methods such as cubic spline estimation, morphology filter and Linear-phase finite impulse response (FIR) least-squares-error digital filter, the experimental results on 50 simulated and 500 real pulse signals demonstrate the power of CAF filter both in removing baseline wander and in preserving the diagnostic information of pulse waveforms. This CAF filter also can be used to remove the baseline wander of other physiological signals, such as ECG and so on.
Original languageEnglish
Pages (from-to)716-731
Number of pages16
JournalComputers in Biology and Medicine
Volume37
Issue number5
DOIs
Publication statusPublished - 1 May 2007

Keywords

  • Baseline wander
  • Cubic spline estimation
  • FIR filter
  • Meyer wavelet
  • Pulse diagnosis
  • Pulse waveform

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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