title: Signal denoising and baseline correction by discrete wavelet transform for microchip capillary electrophoresis.
abstract: Signal denoising and baseline correction using discrete wavelet transform (DWT) are described for microchip capillary electrophoresis (MCE). DWT was performed on an electropherogram describing a separation of nine tetramethylrohodamine-5-isothiocyanate labeled amino acids, following MCE with laser-induced fluorescence detection, using Daubechies 5 wavelet at a decomposition level of 6. The denoising efficiency was compared with, and proved to be superior to, other commonly used denoising techniques such as Fourier transform, Savitzky-Golay smoothing and moving average, in terms of noise removal and peak preservation by directly visual inspection. Novel strategies for baseline correction were proposed, with a special interest in baseline drift that frequently occurred in chromatographic and electrophoretic separations.
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry; D019075:Electrophoresis, Capillary / Q000295:instrumentation / Q000379:methods*; D005456:Fluorescent Dyes; D005583:Fourier Analysis; D008832:Microchemistry / Q000295:instrumentation / Q000379:methods*; D012235:Rhodamines; D012815:Signal Processing, Computer-Assisted
chemical_list: D000596:Amino Acids; D005456:Fluorescent Dyes; D012235:Rhodamines; C009434:tetramethylrhodamine isothiocyanate