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Abstract

Aiming at the problem that the wavelet threshold algorithm is poor denoising effect in traditional pulse measuring instrument, an adaptive filtering algorithm of improved wavelet threshold function and threshold estimation is proposed in this system. This algorithm is used to eliminate the constant deviation of soft threshold function and the discontinuous shortcomings of hard threshold function by constructing a new threshold function and threshold estimation method and adjusting the adaptive adjustment coefficient, thus filtering out the interference noise in photoplethysmograph signals. The light intensity signals acquired by the photoelectric sensor are sequentially processed by signal amplifying circuit and filter circuit, the photoplethysmography signals are transmitted into LPC2103 for further processing, the results are displayed on the LCD screen. Experiments show that the improved wavelet threshold algorithm not only preserves the useful signal, but also avoids the oscillation. The algorithm is employed to denoise the pulse wave, which effectively improves the accuracy of the pulse measuring instrument.

Keywords

Wavelet threshold algorithm pulse measuring apparatus photoplethysmography embedded

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References

Zhang

Y.B.

Chen

X.M.

et al., Study on noninvasive continuous blood pressure measurement based on multiple sensors, Electronic Technology Applications 42(5) (2016), 64–67.

Bao

Y.X.

Gao

et al., Continuous blood pressure measurement system based on pulse wave conduction time, Biomedical Engineering Research 35(1) (2016), 41–45.

Huang

W.S.

, Design and implementation of pulse measuring instrument based on single chip microcomputer, Small and Medium Enterprise Management and Technology (9) (2016), 150–151.

Ouyang

Cheng

and Wang

, Application of improved wavelet threshold algorithm in ECG signal denoising, Computer Engineering and Applications 51(4) (2015), 213–217.

Zhang

G.D.

Shi

W.J.

et al., Wavelet denoising algorithm based on new threshold function, Microcomputers and Applications 35(17) (2016), 20–22.

Zhang

X.Y.

and Tu Erhong Jiang

A.B.D.K.L.M.

, Improvement of threshold image denoising algorithm based on wavelet transform, Computer Technology and Development 27(3) (2017), 81–84.

Chen

X.X.

Wang

Y.J.

and Liu

, Wavelet depth denoising method, Laser and Infrared 42(1) (2012), 105–110.

Xia

H.B.

Shen

L.L.

et al., An improved wavelet threshold crack image denoising method, Electronic Design Engineering 21(18) (2013), 130–132.

Jiang

and Ban

, Improvement and simulation of wavelet threshold denoising function, China Electric Power Education (35) (2014), 138–139.

10.

Mitsuru

Reiko

and Kuniharu

, A new evaluation method for image noise reduction and usefulness of the spatially adaptive wavelet thresholding method for CT images, Australasian Physical & Engineering Sciences in Medicine 35(4) (2012), 475–483.

11.

Wang

Cheng

et al., An improved wavelet threshold image denoising method, Computer and Modernization (4) (2015), 65–69.

12.

Cheng

W.B.

and Chen

J.S.

, A new wavelet packet image denoising method with improved threshold, Journal of Xi’an University of Science and Technology 30(4) (2010), 479–483.

13.

H.E.

and Zhou

J.Y.

, Design of pulse measuring instrument based on AT89C51 single chip microcomputer, Shanxi Electronic Technology (2) (2015), 3–5.

14.

Tian

J.D.

, Research on embedded remote health monitoring system based on ARM, Xi’an Engineering University, China, 2016.

15.

Huang

B.R.

Yang

Y.N.

Yang

S.P.

et al., Design of pulse frequency meter based on STC89C51, Information Technology (10) (2016), 74–75.

16.

Sampath

and Sumithira

T.R.

, ECG morphological marking using discrete wavelet transform, Intelligent Decision Technologies 10(4) (2016), 373–383.

17.

Shi

X.D.

C.Y.

Zhao

H.X.

et al., Research on noise reduction of weak signals in grounding reliability testing of aircraft cable shield, Journal of Computational Methods in Sciences and Engineering 15(3) (2015), 405–414.

18.

Zhang

W.J.

Liu

Z.J.

and Yin

J.C.

, Time-delay wavelet network predictor based on sensitivity analysis with application to predictive ship course control, Journal of Computational Methods in Sciences and Engineering 16(2) (2016), 391–402.

Application of an improved wavelet threshold algorithm in pulse measuring instrument

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