|Table of Contents|

 Removal of baseline drift of pulse wave based on smoothness prior(PDF)

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

Issue:
2018年第10期
Page:
1197-1202
Research Field:
医学信号处理与医学仪器
Publishing date:

Info

Title:
 Removal of baseline drift of pulse wave based on smoothness prior
Author(s):
SU Zhigang12 LÜ Jiangbo1 HAO Jingtang2
 1. Tianjin Key Lab for Advanced Signal and Image Processing, Civil Aviation University of China, Tianjin 300300, China; 2. Sino-European Institute of Aviation Engineering, Civil Aviation University of China, Tianjin 300300, China
Keywords:
 Keywords: pulse wave baseline draft smoothness prior regularization parameter signal-to-noise ratio
PACS:
R318.04
DOI:
DOI:10.3969/j.issn.1005-202X.2018.10.017
Abstract:
 Abstract: The pulse wave signal is rich in physiological and pathological information of human body. However, the problem of the baseline drift of pulse wave collected by photoplethysmography is very serious and directly affects the accurate extraction of human physiological parameters. In the field of biological signal processing, the method of removing the baseline drift is complicated and the time for signal processing is too long, which can’t meet the need of real-time processing of the pulse wave. Herein the smoothness prior based on regularized least squares method is firstly proposed to remove the baseline drift of pulse wave. In this method, the cutoff frequency of the smoothness prior under different regularization parameters is analyzed, and the frequency range of the baseline drift signals in the pulse wave signals is also considered to select the appropriate regularization parameters to remove the baseline drift of the pulse wave. Experimental results show that compared with wavelet transform and empirical mode decomposition, the proposed method can effectively remove the baseline drift of the pulse wave, increase the calculation speed and improve the signal-to-noise ratio, which benefits the accurate extraction of the feature points of the pulse wave.

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Last Update: 2018-10-23