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An application of continuous wavelet transform to electrochemical signals for the quantitative analysis

  • İncilay Süslü
  • Erdal Dinç
  • Sacide Altinöz
Conference paper

Abstract

Continuous wavelet transform (CWT) is a new powerful tool for removing noise, irrelevant information and signal baseline correction of voltammograms. In this application, morlet continuous wavelet transforms (ML-CWT) for signal treatments were found to be suitable among the wavelet families. MLCWT approach was applied to the peak current data vectors consisting of 139 data points in the potential range of (−1004) – (−1556) mV versus Ag/AgCl reference electrode. Peak current data for the calibration and prediction steps in the concentration range of 83.0–375.0 µg=mL zafirlukast were obtained by using Osteryoung Square Wave Adsorption Stripping Voltammetry (OSWAdSV).

Three different calibration models namely mean centering calibration (MCC), principal component regression (PCR) and partial least squares (PLS) were constructed by using the relationship between concentration set and CWT-coefficients of the peak current data. The proposed methods were validated by analyzing the synthetic samples and standard addition samples. These methods were successfully applied to the quantitative analysis of zafirlukast in tablets and satisfactory results were reported.

Keywords

Partial Little Square Continuous Wavelet Principal Component Regression Commercial Tablet Piperonyl Butoxide 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [Da92]
    Daubechies, I.: Ten Lectures on Wavelets. Society for Industrial and Applied Mathematics, Philadelphia (1992)MATHGoogle Scholar
  2. [Wa00]
    Walczak, B.: Wavelets in Chemistry. Elsevier Press, Amsterdam, The Netherlands (2000)Google Scholar
  3. [LCG98]
    Leung, A.K., Chau, F.T., Gao, J.: A review on applications of wavelet transform techniques in chemical analysis: 19891997. Chemom. Intell. Lab. Syst., 43, 165–184 (1998)CrossRefGoogle Scholar
  4. [DB04]
    Dinc, E., Baleanu, D.: Application of the wavelet method for the simultaneous quantitative determination of benazepril and hydrochlorothiazide in their mixtures. J.A.OAC Int., 87(4), 834–841 (2004)Google Scholar
  5. [RG00]
    Ren, S., Gao, L.: Simultaneous quantitative analysis of overlapping spectrophotometric signals using wavelet multiresolution analysis and partial least squares ARTICLE Pages. Talanta, 50, 1163–1173 (2000)CrossRefGoogle Scholar
  6. [ZM97]
    Zou, X., Mo, J.: Spline wavelet analysis for voltammetric signals. Anal. Chim. Acta, 340, 115–121 (1997)CrossRefGoogle Scholar
  7. [NWWZLR01]
    Nie, L., Wu, S., Wang, J., Zheng, L., Lin, X., Rui, L.: Continuous wavelet transform and its application to resolving and quantifying the overlapped voltammetric peaks. Anal. Chim. Acta, 450, 185–192 (2001)CrossRefGoogle Scholar
  8. [CHNPSU97]
    Cocchi, M., Hidalgo-de-Cisneros, J.L., Naranjo-Rodriquez, I., Palacios-Santander, J.M., Seeber, R., Ulrici, A.: Multicomponent analysis of electrochemical signals in the wavelet domain. Talanta, 59, 735–749 (2003)CrossRefGoogle Scholar
  9. [DBK04]
    Dinc, E., Baleanu, D., Kanbur, M.: Spectrophotometric multicomponent determination of tetramethrin, propoxur and piperonyl butoxide in insecticide formulation by principal component regression and partial least squares techniques with continuous wavelet transform. Can. J. Anal. Scienc. Spectr., 49(4), 218–225 (2004)Google Scholar
  10. [DOB05]
    Dinc, E., Ozdemir, A., Baleanu, D.: Comparative study of the continuous wavelet transform, derivative and partial least squares methods applied to the overlapping spectra for the simultaneous quantitative resolution of two-component mixtures. J. Pharm. and Biomed. Anal., 37(3), 569–575 (2005)CrossRefGoogle Scholar
  11. [CSHS05]
    Chen, D., Shao, X.G., Hu, B., Su, Q.D.: Simultaneous Wavelength Selection and Outlier Detection in Multivariate Regression of Near-Infrared. Spectra. Anal. Scien., 21(2), 161–166 (2005)MATHGoogle Scholar
  12. [KKSS05]
    Kharintsev, S.S., Kamalova, D.I., Salakhov, M.Kh., Sevastianov, A.A.: Resolution enhancement of composite spectra using wavelet-based derivative spectrometry. Spectr. Acta Part A, 61(1–2), 149–156 (2005)CrossRefGoogle Scholar
  13. [DBUAE04]
    Dinc, E., Baleanu, D., Ustundag, O. Aboul-Enein, H.Y.: Continuous wavelet transformation applied to the simultaneous quantitative analysis of twocomponent mixtures. Pharmazie, 59(8), 618–623 (2004)Google Scholar
  14. [DB00]
    Dinc, E., Baleanu, D.: Multicomponent quantitative resolution of binary mixtures by using continuous wavelet transform. J. AOAC Int., 87(2), 360–365 (2000)Google Scholar
  15. [DB03]
    Dinc, E., Baleanu, D.: Multidetermination of thiamine HCl and pyridoxine HCl in their mixture using continuous daubechies and biorthogonal wavelet analysis. Talanta, 59, 707–717 (2003)CrossRefGoogle Scholar
  16. [FFTMCFS00]
    Ficarra, R., Ficarra, P., Tommasini, S., Melardi, S., Calabro, M.L., Furlanetto, S., Semreen, M.: Determination of zafirlukast, a selective leukotriene antagonist, human plasma by normal-phase high-performance liquid chromatography with uorescence detection. J. Pharm. Biomed. Anal., 23(1), 169–174 (2000)CrossRefGoogle Scholar
  17. [BCC97]
    Bui, K.H., Coleen, M.K., Connie, T.A.: Determination of zafirlukast, a selective leukotriene antagonist, human plasma by normal-phase highperformance liquid chromatography with uorescence detection. J. Chromatogr. B., 696(1), 131–136 (1997)CrossRefGoogle Scholar
  18. [RSS02]
    Radhakrishna, T., Satyanarayana, J., Satyanarayana, A.: Determination of zafirlukast by stability indicating LC and derivative spectrophotometry. J. Pharm. Biomed. Anal., 30(3), 695–703 (2002)CrossRefGoogle Scholar
  19. [SA05a]
    Suslu, I., Altinoz, S.: Electrochemical characteristics of zafirlukast and its determination in pharmaceutical formulations by voltammetric methods. J. Pharm. Biomed. Anal., 39, 535–542 (2005)CrossRefGoogle Scholar
  20. [SA05b]
    Suslu, I., Altinoz, S.: Differential pulse adsorptive stripping voltammetric determination of zafirlukast in pharmaceutical formulations. Anal. Lett., 38, 1625–1639 (2005)CrossRefGoogle Scholar
  21. [EAEMP96]
    European Agency for the Evaluation of Medical Products. ICH Topic Q2B Note for Guidance on Validation of Analytical Procedures: Methodology GPMP/ICH/281/95 (1996)Google Scholar

Copyright information

© Springer 2007

Authors and Affiliations

  • İncilay Süslü
    • 1
  • Erdal Dinç
    • 2
  • Sacide Altinöz
    • 1
  1. 1.Department of Analytical Chemistry, Faculty of PharmacyHacettepe UniversityTurkey
  2. 2.Department of Analytical Chemistry, Faculty of PharmacyAnkara UniversityTandogan, AnkaraTurkey

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