Research of wave filter method of human sphygmus signal

JI Changpeng; ZHAO Lina

doi:10.7510/jgjs.issn.1001-3806.2016.01.010

LASER TECHNOLOGY > 2016 > 40(1): 42-46. > DOI: 10.7510/jgjs.issn.1001-3806.2016.01.010

JI Changpeng, ZHAO Lina. Research of wave filter method of human sphygmus signal[J]. LASER TECHNOLOGY, 2016, 40(1): 42-46. DOI: 10.7510/jgjs.issn.1001-3806.2016.01.010

Citation:

JI Changpeng, ZHAO Lina. Research of wave filter method of human sphygmus signal[J]. LASER TECHNOLOGY, 2016, 40(1): 42-46. DOI: 10.7510/jgjs.issn.1001-3806.2016.01.010

Citation:

JI Changpeng, ZHAO Lina. Research of wave filter method of human sphygmus signal[J]. LASER TECHNOLOGY, 2016, 40(1): 42-46. DOI: 10.7510/jgjs.issn.1001-3806.2016.01.010

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Research of wave filter method of human sphygmus signal

JI Changpeng¹,
ZHAO Lina²

1.
School of Electronics and Information Engineering, Liaoning Technical University, Huludao 125105, China;
2.
Institute of Graduate, Liaoning Technical University, Huludao 125105, China

More Information

Received Date: October 13, 2014
Revised Date: November 11, 2014
Published Date: January 24, 2016

Graphical Abstract

Abstract

Abstract

In order to reduce the disturbance of noise on human sphygmus signal and improve the precision of data acquisition, a new improved filtering method was proposed. Based on the characteristics of sphygmus signal and noise, by using empirical mode decomposition method, the appropriate wavelet basis was selected, the wavelet threshold function was improved and a modal coefficients was built suitable for the filtering of a sphygmus signal. And then, sphygmus signals were filtered by the structural modal coefficient. After theoretical analysis and experimental verification, ideal experimental data was obtained. The results show that the improved threshold algorithm not only overcomes the limitations of soft threshold and hard threshold, but also overcomes the edge effect problems effectively which is generated by Fourier transform. At the same time, combining with the empirical mode decomposition method, the filtering errors of low frequency noise are weakened and the adaptability of wavelet transform is enhanced. Compared with the traditional filtering methods, the new method can suppress noise effectively and help to improve the signal-to-noise ratio.
- signal processing,
- human sphygmus signal,
- wavelet transform,
- empirical mode decomposition,
- modal coefficient

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References (18)

References

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