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Title: Baseline wander correction in pulse waveforms using wavelet-based cascaded adaptive filter
Authors: Xu, L
Zhang, D 
Wang, K
Li, N
Wang, X
Keywords: Baseline wander
Cubic spline estimation
FIR filter
Meyer wavelet
Pulse diagnosis
Pulse waveform
Issue Date: 2007
Publisher: Pergamon Press
Source: Computers in biology and medicine, 2007, v. 37, no. 5, p. 716-731 How to cite?
Journal: Computers in biology and medicine 
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.
ISSN: 0010-4825
EISSN: 1879-0534
DOI: 10.1016/j.compbiomed.2006.06.014
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