Parameter Estimation of Photoacoustic Signal for Glucose Solutions Using Laplace Wavelet Correlation Filtering and Least Square Estimation

Abstract:

In photoacoustic (PA) technology, piezoelectrical transducer (PZT) is the most frequently used detector for the PA signal generated by weakly absorbing liquids. Although PZT has high sensitivity, its output signals are distorted and become exponentially damped sinusoidal signal [, which is a barrier to extract correct information of glucose. Therefore it is necessary to find a proper way to extract glucose information. In this paper, a method of parameter estimation based on Laplace wavelet correlation filtering and Least Square Estimation is proposed to extract the information of PA signals, which includes signal decomposition, fitting and glucose parameter extraction. The Laplace wavelet correlation filtering is introduced to decompose piezoelectrical signals into impulse responses of single mode subsystems [2], followed by a Least Square Estimator to fit PA signal and estimate parameters of the exponentially damped sinusoidal model [3]. Good agreement between the fitting model and the PA signal is obtained. Experiments are carried out on finding meaningful parameters indicating glucose among estimated parameters of the exponentially damped sinusoidal model.

• Periodical: Applied Mechanics and Materials (Volumes 475-476)
• Pages: 225-235
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.475-476.225
• Online since: December 2013
• Authors: Qian Zhou, Si Wei Zhao, Jia Si Wei, Hao Yan, Hui Zhao*
• Keywords: Glucose, Laplace Wavelet, Least Square Estimation, Photoacoustic

References

[1] Fu, S. W., et al. Ultrasonic transducer study for photoacoustic calorimetry. Ultrasonics Symposium, 1995. Proceedings., 1995 IEEE. Vol. 2. IEEE, (1995).

DOI: 10.1109/ultsym.1995.495702

[2] Jiang, Qing, et al. A method of characteristic impulse identification based on Laplace wavelet matching., Image and Signal Processing (CISP), 2010 3rd International Congress on. Vol. 8. IEEE, (2010).

DOI: 10.1109/cisp.2010.5647139

[3] Kay, Steven M. Fundamentals of Statistical signal processing, volume I: Estimation theory. Prentice Hall PTR, (1998).

[4] MacKenzie, Hugh A., et al. Advances in photoacoustic noninvasive glucose testing., Clinical chemistry 45. 9 (1999): 1587-1595.

[5] Kottmann, Jonas, et al. Mid-infrared photoacoustic sensing of glucose in keratinocyte solutions., Lasers and Electro-Optics Europe (CLEO EUROPE/EQEC), 2011 Conference on and 12th European Quantum Electronics Conference. IEEE, (2011).

DOI: 10.1109/cleoe.2011.5943084

[6] Ren, Zhong, et al. Exploration of noninvasive determination of blood glucose concentration by using photoacoustic technique., ISPDI 2013-Fifth International Symposium on Photoelectronic Detection and Imaging. International Society for Optics and Photonics, (2013).

DOI: 10.1117/12.2033271

[7] Hodgson, P., et al. Application of pulsed laser photoacoustic sensors in monitoring oil contamination in water., Sensors and Actuators B: Chemical 29. 1 (1995): 339-344.

DOI: 10.1016/0925-4005(95)01704-6

[8] SONG, Zhiyuan, et al. The regularization processing of signal deconvolution in photoacoustic signal recovery., Progress in biomedical optics and imaging 8. 16 (2007).

[9] Heritier, Jean-Marc. Electrostrictive limit and focusing effects in pulsed photoacoustic detection., Optics Communications 44. 4 (1983): 267-272.

DOI: 10.1016/0030-4018(83)90135-9

[10] Schurig, D. A., et al. Signal analysis of transients in pulsed photoacoustic spectroscopy., Review of scientific instruments 64. 2 (1993): 363-373.

DOI: 10.1063/1.1144258

[11] Platt, Stephen Robert. Electric power generation within orthopaedic implants using piezoelectric ceramics. Diss. University of Nebraska-Lincoln, (2003).

[12] Freudinger, Lawrence C., Rick Lind, and Martin J. Brenner. Correlation filtering of modal dynamics using the Laplace wavelet., Society for Experimental Mechanics, Inc, 16 th International Modal Analysis Conference. Vol. 2. (1998).