Abstract

Pulse oximeter is widely used in the monitoring of blood oxygen in clinic for its convenience and efficiency. However, synchronizing light source flashing with data collecting is required, otherwise the separation of the data from different LEDs will fail. More importantly, synchronous acquisition makes the pulse oximetry system vulnerable. Meanwhile, the pulse waveform extraction is a crucial procedure in the measurement. Hence, in this paper, an asynchronous acquisition pulse oximetry system based on wavelet transform has been built. PhotoPlethysmoGraph (PPG) and photoelectric detection technology are applied in our homemade system. The adaptive soft-threshold de-noising is realized by Stein's Unbiased Risk Estimate (SURE). The principle and system configuration are described. The preliminary experiment results from wavelet transforms and Fourier transforms are compared. The results show that our homemade system is adaptive, accurate, robust and simple.

© 2013 Optical Society of America

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References

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  1. T. Aoyagi, M. Kishi, K. Yamaguchi, and S. Watanabe, “Improvement of the earpiece oximeter,” in Abstracts of the Japanese Society of Medical Electronics and Biological Engineering (Japanese Society of Medical Electronics and Biological Engineering, Tokyo, 1974), pp. 90–91.
  2. S. A. Wilber, “Blood constituent measuring device and method,” U.S. Patent No. 4,407,290, Washington, DC: U.S. Patent and Trademark Office (1983).
  3. P. S. Addison and J. N. Watson, “A novel time–frequency-based 3D Lissajous figure method and its application to the determination of oxygen saturation from the photoplethysmogram,” Meas. Sci. Technol.15(11), L15–L18 (2004).
    [CrossRef]
  4. Y. S. Yan and Y. T. Zhang, “An efficient motion-resistant method for wearable pulse oximeter,” IEEE Trans. Inf. Technol. Biomed.12(3), 399–405 (2008).
    [CrossRef] [PubMed]
  5. F. U. Dowla, P. G. Skokowski, and R. R. Leach, Jr., “Neural networks and wavelet analysis in the computer interpretation of pulse oximetry data,” in Proceedings of IEEE Conference on Neural Networks for Signal Processing (IEEE Signal Processing Society Workshop, Kyoto, 1996), pp. 527–536.
    [CrossRef]
  6. S. Lee, B. L. Ibey, W. Xu, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Processing of pulse oximeter data using discrete wavelet analysis,” IEEE Trans. Biomed. Eng.52(7), 1350–1352 (2005).
    [CrossRef] [PubMed]
  7. Y. Yong-sheng, C. Y. Poon Carmen, and Z. Yuan-ting, “Reduction of motion artifact in pulse oximetry by smoothed pseudo Wigner-Ville distribution,” J. NeuroEng. Rehabil.2(3), 9 (2005).
  8. X. U. Kexin, G. A. O. Feng, and Z. H. A. O. Huijuan, Biomedical Photonics, 2nd ed. (Science Press, 2010), p. 182.
  9. C. M. Stein, “Estimation of the mean of a multivariate normal distribution,” Ann. Stat.9(6), 1135–1151 (1981).
    [CrossRef]
  10. D. L. Donoho and I. M. Johnstone, “Adapting to unknown smoothness via wavelet shrinkage,” J. Am. Stat. Assoc.90(432), 1200–1224 (1995).
    [CrossRef]
  11. J. A. Dempsey and P. D. Wagner, “Exercise-induced arterial hypoxemia,” J. Appl. Physiol.87(6), 1997–2006 (1999).
    [PubMed]

2008 (1)

Y. S. Yan and Y. T. Zhang, “An efficient motion-resistant method for wearable pulse oximeter,” IEEE Trans. Inf. Technol. Biomed.12(3), 399–405 (2008).
[CrossRef] [PubMed]

2005 (2)

S. Lee, B. L. Ibey, W. Xu, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Processing of pulse oximeter data using discrete wavelet analysis,” IEEE Trans. Biomed. Eng.52(7), 1350–1352 (2005).
[CrossRef] [PubMed]

Y. Yong-sheng, C. Y. Poon Carmen, and Z. Yuan-ting, “Reduction of motion artifact in pulse oximetry by smoothed pseudo Wigner-Ville distribution,” J. NeuroEng. Rehabil.2(3), 9 (2005).

2004 (1)

P. S. Addison and J. N. Watson, “A novel time–frequency-based 3D Lissajous figure method and its application to the determination of oxygen saturation from the photoplethysmogram,” Meas. Sci. Technol.15(11), L15–L18 (2004).
[CrossRef]

1999 (1)

J. A. Dempsey and P. D. Wagner, “Exercise-induced arterial hypoxemia,” J. Appl. Physiol.87(6), 1997–2006 (1999).
[PubMed]

1995 (1)

D. L. Donoho and I. M. Johnstone, “Adapting to unknown smoothness via wavelet shrinkage,” J. Am. Stat. Assoc.90(432), 1200–1224 (1995).
[CrossRef]

1981 (1)

C. M. Stein, “Estimation of the mean of a multivariate normal distribution,” Ann. Stat.9(6), 1135–1151 (1981).
[CrossRef]

Addison, P. S.

P. S. Addison and J. N. Watson, “A novel time–frequency-based 3D Lissajous figure method and its application to the determination of oxygen saturation from the photoplethysmogram,” Meas. Sci. Technol.15(11), L15–L18 (2004).
[CrossRef]

Coté, G. L.

S. Lee, B. L. Ibey, W. Xu, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Processing of pulse oximeter data using discrete wavelet analysis,” IEEE Trans. Biomed. Eng.52(7), 1350–1352 (2005).
[CrossRef] [PubMed]

Dempsey, J. A.

J. A. Dempsey and P. D. Wagner, “Exercise-induced arterial hypoxemia,” J. Appl. Physiol.87(6), 1997–2006 (1999).
[PubMed]

Donoho, D. L.

D. L. Donoho and I. M. Johnstone, “Adapting to unknown smoothness via wavelet shrinkage,” J. Am. Stat. Assoc.90(432), 1200–1224 (1995).
[CrossRef]

Ericson, M. N.

S. Lee, B. L. Ibey, W. Xu, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Processing of pulse oximeter data using discrete wavelet analysis,” IEEE Trans. Biomed. Eng.52(7), 1350–1352 (2005).
[CrossRef] [PubMed]

Ibey, B. L.

S. Lee, B. L. Ibey, W. Xu, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Processing of pulse oximeter data using discrete wavelet analysis,” IEEE Trans. Biomed. Eng.52(7), 1350–1352 (2005).
[CrossRef] [PubMed]

Johnstone, I. M.

D. L. Donoho and I. M. Johnstone, “Adapting to unknown smoothness via wavelet shrinkage,” J. Am. Stat. Assoc.90(432), 1200–1224 (1995).
[CrossRef]

Lee, S.

S. Lee, B. L. Ibey, W. Xu, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Processing of pulse oximeter data using discrete wavelet analysis,” IEEE Trans. Biomed. Eng.52(7), 1350–1352 (2005).
[CrossRef] [PubMed]

Poon Carmen, C. Y.

Y. Yong-sheng, C. Y. Poon Carmen, and Z. Yuan-ting, “Reduction of motion artifact in pulse oximetry by smoothed pseudo Wigner-Ville distribution,” J. NeuroEng. Rehabil.2(3), 9 (2005).

Stein, C. M.

C. M. Stein, “Estimation of the mean of a multivariate normal distribution,” Ann. Stat.9(6), 1135–1151 (1981).
[CrossRef]

Wagner, P. D.

J. A. Dempsey and P. D. Wagner, “Exercise-induced arterial hypoxemia,” J. Appl. Physiol.87(6), 1997–2006 (1999).
[PubMed]

Watson, J. N.

P. S. Addison and J. N. Watson, “A novel time–frequency-based 3D Lissajous figure method and its application to the determination of oxygen saturation from the photoplethysmogram,” Meas. Sci. Technol.15(11), L15–L18 (2004).
[CrossRef]

Wilson, M. A.

S. Lee, B. L. Ibey, W. Xu, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Processing of pulse oximeter data using discrete wavelet analysis,” IEEE Trans. Biomed. Eng.52(7), 1350–1352 (2005).
[CrossRef] [PubMed]

Xu, W.

S. Lee, B. L. Ibey, W. Xu, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Processing of pulse oximeter data using discrete wavelet analysis,” IEEE Trans. Biomed. Eng.52(7), 1350–1352 (2005).
[CrossRef] [PubMed]

Yan, Y. S.

Y. S. Yan and Y. T. Zhang, “An efficient motion-resistant method for wearable pulse oximeter,” IEEE Trans. Inf. Technol. Biomed.12(3), 399–405 (2008).
[CrossRef] [PubMed]

Yong-sheng, Y.

Y. Yong-sheng, C. Y. Poon Carmen, and Z. Yuan-ting, “Reduction of motion artifact in pulse oximetry by smoothed pseudo Wigner-Ville distribution,” J. NeuroEng. Rehabil.2(3), 9 (2005).

Yuan-ting, Z.

Y. Yong-sheng, C. Y. Poon Carmen, and Z. Yuan-ting, “Reduction of motion artifact in pulse oximetry by smoothed pseudo Wigner-Ville distribution,” J. NeuroEng. Rehabil.2(3), 9 (2005).

Zhang, Y. T.

Y. S. Yan and Y. T. Zhang, “An efficient motion-resistant method for wearable pulse oximeter,” IEEE Trans. Inf. Technol. Biomed.12(3), 399–405 (2008).
[CrossRef] [PubMed]

Ann. Stat. (1)

C. M. Stein, “Estimation of the mean of a multivariate normal distribution,” Ann. Stat.9(6), 1135–1151 (1981).
[CrossRef]

IEEE Trans. Biomed. Eng. (1)

S. Lee, B. L. Ibey, W. Xu, M. A. Wilson, M. N. Ericson, and G. L. Coté, “Processing of pulse oximeter data using discrete wavelet analysis,” IEEE Trans. Biomed. Eng.52(7), 1350–1352 (2005).
[CrossRef] [PubMed]

IEEE Trans. Inf. Technol. Biomed. (1)

Y. S. Yan and Y. T. Zhang, “An efficient motion-resistant method for wearable pulse oximeter,” IEEE Trans. Inf. Technol. Biomed.12(3), 399–405 (2008).
[CrossRef] [PubMed]

J. Am. Stat. Assoc. (1)

D. L. Donoho and I. M. Johnstone, “Adapting to unknown smoothness via wavelet shrinkage,” J. Am. Stat. Assoc.90(432), 1200–1224 (1995).
[CrossRef]

J. Appl. Physiol. (1)

J. A. Dempsey and P. D. Wagner, “Exercise-induced arterial hypoxemia,” J. Appl. Physiol.87(6), 1997–2006 (1999).
[PubMed]

J. NeuroEng. Rehabil. (1)

Y. Yong-sheng, C. Y. Poon Carmen, and Z. Yuan-ting, “Reduction of motion artifact in pulse oximetry by smoothed pseudo Wigner-Ville distribution,” J. NeuroEng. Rehabil.2(3), 9 (2005).

Meas. Sci. Technol. (1)

P. S. Addison and J. N. Watson, “A novel time–frequency-based 3D Lissajous figure method and its application to the determination of oxygen saturation from the photoplethysmogram,” Meas. Sci. Technol.15(11), L15–L18 (2004).
[CrossRef]

Other (4)

X. U. Kexin, G. A. O. Feng, and Z. H. A. O. Huijuan, Biomedical Photonics, 2nd ed. (Science Press, 2010), p. 182.

F. U. Dowla, P. G. Skokowski, and R. R. Leach, Jr., “Neural networks and wavelet analysis in the computer interpretation of pulse oximetry data,” in Proceedings of IEEE Conference on Neural Networks for Signal Processing (IEEE Signal Processing Society Workshop, Kyoto, 1996), pp. 527–536.
[CrossRef]

T. Aoyagi, M. Kishi, K. Yamaguchi, and S. Watanabe, “Improvement of the earpiece oximeter,” in Abstracts of the Japanese Society of Medical Electronics and Biological Engineering (Japanese Society of Medical Electronics and Biological Engineering, Tokyo, 1974), pp. 90–91.

S. A. Wilber, “Blood constituent measuring device and method,” U.S. Patent No. 4,407,290, Washington, DC: U.S. Patent and Trademark Office (1983).

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Figures (10)

Fig. 1
Fig. 1

System arrangement.

Fig. 2
Fig. 2

Origin data (scatter diagram).

Fig. 3
Fig. 3

Threshold selection flowchart.

Fig. 4
Fig. 4

Signal processing flowchart via DWT.

Fig. 5
Fig. 5

Signal processing flowchart via FFT.

Fig. 6
Fig. 6

Red (660 nm) signal with noise.

Fig. 7
Fig. 7

Infrared (940 nm) signal with noise.

Fig. 8
Fig. 8

Pulse wave with baseline drift. (a) Signal extracted via WT; (b) Signal extracted via FT.

Fig. 9
Fig. 9

Baseline drift. (a) Baseline drift extracted via WT; (b) Baseline drift extracted via FT.

Fig. 10
Fig. 10

Pulse wave. (a) Pulse wave extracted via DWT; (b) Pulse wave extracted via FFT.

Tables (1)

Tables Icon

Table 1 Result of Each Method

Equations (15)

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Functional Sa O 2 = Hb O 2 Hb O 2 +Hb ×100%,
Sa O 2 =a+b Δ A 1 Δ A 2 =a+bR,
W T s (j,k)= R s(t) φ ¯ j,k (t)dt ,
φ j,k (t)= a 0 j/2 φ( a 0 j tk),
SURE(p(WT))=d σ 2 + g(WT) 2 +2 σ 2 n s n g i (WT),
E p(WT)pulse 2 =E{SURE(p(WT))},
η(WT)={ WTsgn(WT)ST , | WT |>ST 0 , | WT |ST ,
f(t)= j,k η j,k φ j,k (t) ,
FT= j=1 N s(t) ω N (j1)(k1) ,
ω N =exp[(2πi)/N]
f=(1/N) k=1 N F ω N (j1)(k1) ,
ΔA= AC DC ,
Sa O 2 =a+b Δ A 1 Δ A 2 =a+bR=a+b A C 1 /D C 1 A C 2 /D C 2 ,
d(Sa O 2 )= b×D C 2 A C 2 ×D C 1 [d(A C 1 ) 1 A C 2 d(A C 2 )]
d(Sa O 2 )= b×D C 2 ×d(A C 1 ) A C 2 ×D C 1 (1 1 A C 2 ).

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