Absorption spectrophotometry signal de-noising using invariant wavelets
Filtrado de señales en espectrofotometría de absorción mediante wavelets invariantes a la traslación
DOI:
https://doi.org/10.15446/ing.investig.v31n3.26412Keywords:
absorption spectrophotometry, signal filtering, invariant wavelet, biological substance detection (en)espectrofotometría de absorción, filtrado de señales, wavelets invariantes a la traslación, detección de sustancias biológicas (es)
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Diseases such as cancer, hepatitis and AIDS cause body fluid concentration and amount to become modified; their measurement can thus be useful as a diagnostic technique. Spectroscopy is one of the most widely used techniques for biological substance detection and quantification. The presence of unwanted signals is the main limiting factor for sensitivity and quality; this is called noise. Noise has different backgrounds which range from physical assumptions to environmental influence. Eliminating or reducing noise in spectroscopy has thus been studied for many years and the applicability of wavelet transform has been demonstrated in recent decades. This paper presents invariant wavelet transform for increasing signal to noise ratio in spectrophotometer signals and thus improve the quality of spectrophotometric analysis and biological substance quantification. The proposed technique was applied to artificially-generated signals and signals from two spectrometers, one having a continuum source and another with a laser radiation source. The results obtained with this technique were compared to those obtained from traditional filters: Gaussian, Wiener and orthogonal wavelets. This technique's main advantages are a substantial increase in signal to noise ratio and preservation of spectral peak location and width. These advantages increase biological substance detection and quantification quality and accuracy and allow automatic analysis of the spectrum. They can also lead to better understanding of experimental limitations and allow a quantitative study of the influence of changes in substance concentration in related diseases.
Enfermedades como cáncer, hepatitis y sida, entre otras, ocasionan que la concentración y cantidad de algunas sustancias en fluidos corporales se modifique, por lo que su medición puede servir como técnica diagnóstica. Entre las técnicas más utilizadas para la detección y cuantificación de sustancias biológicas se encuentra la espectroscopía. El principal factor que limita la sensibilidad y calidad en la medida es la presencia de señales indeseadas, denominadas ruido. El ruido tiene diferentes orígenes, los cuales van desde los supuestos físicos hasta la influencia ambiental. Eliminar o reducir el ruido en espectroscopía ha sido objeto de estudio durante muchos años y en los últimos lustros se ha demostrado la aplicabilidad de la transformada wavelet con dicho propósito. Este trabajo presenta una transformada wavelet invariante a la traslación como una alternativa para aumentar la relación señal a ruido en señales provenientes de espectrofotómetros y por ende mejorar la calidad del análisis espectrofotométrico y la cuantificación de sustancias biológicas. La técnica propuesta se aplicó a señales generadas artificialmente y provenientes de dos espectrofotómetros, uno con fuente de radiación continua y otro con fuente de radiación láser. Los resultados obtenidos con esa técnica se compararon con los obtenidos a partir de filtros tradicionales: gaussianos, Wiener y wavelets ortogonales. Las principales ventajas derivadas de la aplicación de esta técnica son: un sustancial aumento de la relación señal a ruido y la preservación de la ubicación y el ancho de los picos espectrales. Estas ventajas incrementan la calidad y veracidad en el proceso de detección y cuantificación de sustancias biológicas y posibilitan un análisis automático del espectro. Además, conducirán a comprender las limitaciones experimentales y permitirán un estudio cuantitativo sobre la influencia de los cambios en la concentración de una sustancia determinada en enfermedades relacionadas.
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